Search results for: tree species selection

Authors: Serier Bouchenak NORA, Bouguerni ABDELMADJID

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Algeria is a Mediterranean country which provides an ideal habitat for a wide range of species of medicinal plants. The objective of this current work is to extract the gel contained in the leaves of Aloe vera in order to formulate an oral gel as a prebiotic and see its effects on probiotics (lactic and pseudo lactic bacteria and bifido bacterium). Aloe vera polysaccharid extract is a matrix mainly composed of non-digestible oligosaccharids or slow-fermentation polysaccharids, as this produces a lower pH. The behavior of Aloe vera during in vitro fermentation of the colon was similar to that of lactulose, indicating the possibility of using Aloe vera and its polysaccharids extracts as a prebiotic. The microbiological control of the two kinds of bacteria (bifidobacteria and staphylococci) has demonstrated the gel capacity to stimulate them by these bioactive compounds. The generation time of Bifidobacteria in fermented milk with added prebiotic Aloe vera gel is 80.408 min with a µ growth rate equal to 0.012 min -1. The doubling time is 61.459 min with a growth rate µ equal to 0.016 min -1 for the Streptococcus sp. species.

Keywords: aloe vera, probiotics, prebiotics, growth rate, bifidobacteria

Procedia PDF Downloads 66

Authors: Mohammad Mukarram, M. Masroor A. Khan, Daniel Kurjak, Marek Fabrika

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Lemongrass (Cymbopogon flexuosus (Steud.) Wats) is an aromatic grass with great industrial potential. It is cultivated for its essential oil (EO), which has great economic value due to its numerous medicinal, cosmetic, and culinary applications. The present study had the goal to evaluate whether the combined application of silicon nanoparticles (SiNPs) 150 mg L⁻¹ and irradiated chitosan (ICH) 120 mg L⁻¹ can upgrade lemongrass crop and render enhanced growth and productivity. The analyses of growth and photosynthetic parameters, leaf-nitrogen, and reactive oxygen species metabolism, as well as the content of total essential oil, indicated that combined foliar sprays of SiNPs and ICH can significantly (p≤0.05) trigger a general activation of lemongrass metabolism. Overall, the data indicate that concomitant SiNPs and ICH application elicit lemongrass physiology and defence system, and opens new possibilities for their biotechnological application on other related plant species with agronomic potential.

Keywords: photosynthesis, Cymbopogon, antioxidant metabolism, essential oil, ROS, nanoparticles, polysaccharides

Procedia PDF Downloads 79

Authors: Imad Eddine Rezouani, Khalil Draidi, Badis bakhouche, Selman Anes Chabani

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The Algerian coast is an important site for wintering and migratory birds. Four species of shorebirds were surveyed, including Kentish plover Charadrius alexandrinus, Little ringed plover Charadrius dubius, Common ringed plover Charadrius hiaticula, and black-winged stilt Himantopus hilarious in three different sites, two important wetlands: Reghaia lake and Macta and a small area Sublette promenade to provide a new data about time activity budget. The study found a higher frequency of abundance in April during the study period (February to May), with a mean of 49. Estimating the temporal activity budget of these coastal birds, it was found that there were three main activities in different proportions between males and females: Pecking (29.51 ％) for males, (26.59％) for females, Looking above (28.01％) for males, (19.54 ％) for females And Away (9.95％) for males, (11.75％), contrarily the two previous one. Differences between study areas revealed differences in species behavior and distribution.

Keywords: wetland, behavioral, algerian coast, shorebirds, time budget activity

Procedia PDF Downloads 59

Authors: Chetan Mahawar, Sarath Chandran, Sridhar Panigrahi, V. P. Shaji

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The ever-growing advancement in space exploration has led to an alarming concern for space debris removal as it restricts further launch operations and adventurous space missions; hence numerous studies have come up with technologies for re-entry predictions and material selection processes for mitigating space debris. The selection of material and operating conditions is determined with the objective of lightweight structure and ability to demise faster subject to spacecraft survivability during its mission. Since the demisability of spacecraft depends on evolving thermal material properties such as emissivity, specific heat capacity, thermal conductivity, radiation intensity, etc. Therefore, this paper presents the analysis of evolving thermal material properties of spacecraft, which affect the demisability process and thus estimate demise time using the demisability model by incorporating evolving thermal properties for sensible heating followed by the complete or partial break-up of spacecraft. The demisability analysis thus concludes the best suitable spacecraft material is based on the least estimated demise time, which fulfills the criteria of design-for-survivability and as well as of design-for-demisability.

Keywords: demisability, emissivity, lightweight, re-entry, survivability

Procedia PDF Downloads 110

Authors: Min Wang, Sergey Utev

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The lessons from the 2007-09 global financial crisis have driven scientific research, which considers the design of new methodologies and financial models in the global market. The quantum mechanics approach was introduced in the unpredictable stock market modeling. One famous quantum tool is Feynman path integral method, which was used to model insurance risk by Tamturk and Utev and adapted to formalize the path-dependent option pricing by Hao and Utev. The research is based on the path-dependent calculation method, which is motivated by the Feynman path integral method. The path calculation can be studied in two ways, one way is to label, and the other is computational. Labeling is a part of the representation of objects, and generating functions can provide many different ways of representing share price paths. In this paper, the recent works on graphical theoretical construction of individual share price path via matroid is presented. Firstly, a study is done on the knowledge of matroid, relationship between lattice path matroid and Tutte polynomials and ways to connect points in the lattice path matroid and Tutte polynomials is suggested. Secondly, It is found that a general binary tree can be validly constructed from a connected lattice path matroid rather than general lattice path matroid. Lastly, it is suggested that there is a way to represent share price paths via a general binary tree, and an algorithm is developed to construct share price paths from general binary trees. A relationship is also provided between lattice integer points and Tutte polynomials of a transversal matroid. Use this way of connection together with the algorithm, a share price path can be constructed from a given connected lattice path matroid.

Keywords: combinatorial construction, graphical representation, matroid, path calculation, share price, Tutte polynomial

Procedia PDF Downloads 132

Authors: David Adade-Boateng, Benard Fei Baffoe, Colin A. Booth, Michael A. Fullen

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Remediation of diesel fuel, oil and grease in contaminated soils obtained from a mine site in Ghana are explored using rhizoremediation technology with different levels of nutrient amendments (i.e. N (nitrogen) in Compost (0.2, 0.5 and 0.8%), Urea (0.2, 0.5 and 0.8%) and Topsoil (0.2, 0.5 and 0.8%)) for a native species. A Ghanaian native grass species, Paspalum spp. from the Poaceae family, indicative across Sub-Saharan Africa, was selected following the development of essential and desirable growth criteria. Vegetative parts of the species were subjected to ten treatments in a Randomized Complete Block Design (RCBD) in three replicates. The plant-associated microbial community was examined in Paspalum spp. An assessment of the influence of Paspalum spp on the abundance and activity of micro-organisms in the rhizosphere revealed a build-up of microbial communities over a three month period. This was assessed using the MPN method, which showed rhizospheric samples from the treatments were significantly different (P <0.05). Multiple comparisons showed how microbial populations built-up in the rhizosphere for the different treatments. Treatments G (0.2% compost), H (0.5% compost) and I (0.8% compost) performed significantly better done other treatments, while treatments D (0.2% topsoil) and F (0.8% topsoil) were insignificant. Furthermore, treatment A (0.2% urea), B (0.5% urea), C (0.8% urea) and E (0.5% topsoil) also performed the same. Residual diesel and oil concentrations (as total petroleum hydrocarbons, TPH and oil and grease) were measured using infra-red spectroscopy and gravimetric methods, respectively. The presence of single species successfully enhanced the removal of hydrocarbons from soil. Paspalum spp. subjected to compost levels (0.5% and 0.8%) and topsoil levels (0.5% and 0.8%) showed significantly lower residual hydrocarbon concentrations compared to those treated with Urea. A strong relationship (p<0.001) between the abundance of hydrocarbon degrading micro-organisms in the rhizosphere and hydrocarbon biodegradation was demonstrated for rhizospheric samples with treatment G (0.2% compost), H (0.5% compost) and I (0.8% compost) (P <0.001). The same level of amendment with 0.8% compost (N-level) can improve the application effectiveness. These findings have wide-reaching implications for the environmental management of soils contaminated by hydrocarbons in Sub-Saharan Africa. However, it is necessary to further investigate the in situ rhizoremediation potential of Paspalum spp. at the field scale.

Keywords: rhizoremediation, microbial population, rhizospheric sample, treatments

Procedia PDF Downloads 321

Authors: Emily Kislik, Gabriel Mantilla Saltos, Gladys Torres, Mercy Borbor-Córdova

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The Galápagos Marine Reserve (GMR) is an internationally-recognized region of consistent upwelling events, high productivity, and rich biodiversity. Despite its high-nutrient, low-chlorophyll condition, the archipelago has experienced phytoplankton blooms, especially in the western section between Isabela and Fernandina Islands. However, little is known about how climate variability will affect future phytoplankton standing stock in the Galápagos, and no consistent protocols currently exist to quantify phytoplankton biomass, identify species, or monitor for potential harmful algal blooms (HABs) within the archipelago. This analysis investigates physical, chemical, and biological oceanic variables that contribute to algal blooms within the GMR, using 4 km Aqua MODIS satellite imagery and 0.125-degree wind stress data from January 2003 to December 2016. Furthermore, this study analyzes chlorophyll-a concentrations at varying spatial scales— within the greater archipelago, as well as within five smaller bioregions based on species biodiversity in the GMR. Seasonal and interannual trend analyses, correlations, and hotspot identification were performed. Results demonstrate that chlorophyll-a is expressed in two seasons throughout the year in the GMR, most frequently in September and March, with a notable hotspot in the Elizabeth Bay bioregion. Interannual chlorophyll-a trend analyses revealed highest peaks in 2003, 2007, 2013, and 2016, and variables that correlate highly with chlorophyll-a include surface temperature and particulate organic carbon. This study recommends future in situ sampling locations for phytoplankton monitoring, including the Elizabeth Bay bioregion. Conclusions from this study contribute to the knowledge of oceanic drivers that catalyze primary productivity and consequently affect species biodiversity within the GMR. Additionally, this research can inform policy and decision-making strategies for species conservation and management within bioregions of the Galápagos.

Keywords: bioregions, ecological monitoring, phytoplankton, remote sensing

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

Procedia PDF Downloads 111

Authors: Abdulrahman Abdulhamid Arabo, Raji Arabi Bamanga, Mujiburrahman Fadilu, Musa Abubakar, Fatima Abdullahi Shehu, Hafeez Muhammad Yakasai, Nasiru Abdullahi

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The aim of this study was to isolate and identify biosurfactant-producing and diesel alkanes degrading bacteria. For this reason, bacteria isolated from the diesel-contaminated site were screened for their potential to produce biosurfactants and degrade diesel alkanes. Primary selection of diesel degraders was carried out by using the conventional enrichment culture technique, where 12 bacterial strains were isolated based on their ability to grow on minimal media supplemented with diesel as the sole carbon source, which was followed by qualitative screening methods for potential biosurfactant production. Isolate B11 was the only candidate that showed positive signs for drop collapse, foaming, hemolytic test, oil displacement of more than 22 ± 0.05 mm, and emulsification (E24) of 14 ± 0.30%. The effect of various culture parameters (incubation time, diesel concentration, nitrogen source, pH and temperature) on the biodegradation of diesel was evaluated. The optimum incubation time was confirmed to be 120 days for isolate B11, and the optimum PH was confirmed as 8.0 for the isolate; similarly, the optimum temperature was confirmed as 35oC. In addition, diesel oil was used as the sole carbon source for the isolates. The favorable diesel concentration was 12.5 % (v/v) for the isolate. The isolate has shown degradative ability towards Tridecane (C13), dodecane, 2, 6, 10-trimethyl- (C15), Tetradecane (C14), 2,6,10-Trimethyltridecane (C16), Pentadecane (C15). It degraded between 0.27% - 9.65% of individual diesel oil alkanes. The strain has exhibited the potential of degrading diesel oil n-alkanes and was identified as Alcaligenes species strain B11 (MZ027604) using the 16S rRNA. Sequencing.

Keywords: diesel oil, biosurfactant, Alcaligenes sp, biodegradation

Procedia PDF Downloads 104

Authors: Anne Joseph, Yinusa Asiwaju-Bello, Oluwaseun Olabode

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Sustainable administration of groundwater resources tapped in Coastal Plain Sands aquifer in Abesan area, Eastern Dahomey Basin, Southwestern Nigeria necessitates the knowledge of the pattern of groundwater flow in meeting a suitable environmental need for habitation. Thirty hand-dug wells were identified and evaluated to study the groundwater flow dynamics and anionic species distribution in the study area. Topography and water table levels method with the aid of Surfer were adopted in the identification of recharge and discharge zones where six recharge and discharge zones were delineated correspondingly. Dissolved anionic species of HCO3-, Cl-, SO42-and NO3- were determined using titrimetric and spectrophotometric method. The trend of significant anionic concentrations of groundwater samples are in the order Cl- > HCO3-> SO42- > NO3-. The prominent anions in the discharge and recharge area are Cl- and HCO3- ranging from 0.22ppm to 3.67ppm and 2.59ppm to 0.72ppm respectively. Analysis of groundwater head distribution and the groundwater flow vector in Abesan area confirmed that Cl- concentration is higher than HCO3- concentration in recharge zones. Conversely, there is a high concentration of HCO3- than Cl- inland towards the continent; therefore, HCO3-concentration in the discharge zones is higher than the Cl- concentration. The anions were to be closely related to the recharge and discharge areas which were confirmed by comparison of activities such as rainfall regime and anthropogenic activities in Abesan area. A large percentage of the samples showed that HCO3-, Cl-, SO42-and NO3- falls within the permissible limit of the W.H.O standard. Most of the samples revealed Cl- / (CO3- + HCO3-) ratio higher than 0.5 indicating that there is saltwater intrusion imprints in the groundwater of the study area. Gibbs plot shown that most of the samples is from rock dominance, some from evaporation dominance and few from precipitation dominance. Potential salinity and SO42/ Cl- ratios signifies that most of the groundwater in Abesan is saline and falls in a water class found to be insuitable for irrigation. Continuous dissolution of these anionic species may pose a significant threat to the inhabitants of Abesan area in the nearest future.

Keywords: Abessan, Anionic species, Discharge, Groundwater flow, Recharge

Procedia PDF Downloads 119

Authors: Irina Khutsishvili

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In the present research, a decision support methodology for the multi-attribute group decision-making (MAGDM) problem is developed, namely for the selection of investment projects. The objective of the investment project selection problem is to choose the best project among the set of projects, seeking investment, or to rank all projects in descending order. The project selection is made considering a set of weighted attributes. To evaluate the attributes in our approach, expert assessments are used. In the proposed methodology, lingual expressions (linguistic terms) given by all experts are used as initial attribute evaluations, since they are the most natural and convenient representation of experts' evaluations. Then lingual evaluations are converted into trapezoidal fuzzy numbers, and the aggregate trapezoidal hesitant fuzzy decision matrix will be built. The case is considered when information on the attribute weights is completely unknown. The attribute weights are identified based on the De Luca and Termini information entropy concept, determined in the context of hesitant fuzzy sets. The decisions are made using the extended Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method under a hesitant fuzzy environment. Hence, a methodology is based on a trapezoidal valued hesitant fuzzy TOPSIS decision-making model with entropy weights. The ranking of alternatives is performed by the proximity of their distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). For this purpose, the weighted hesitant Hamming distance is used. An example of investment decision-making is shown that clearly explains the procedure of the proposed methodology.

Keywords: In the present research, a decision support methodology for the multi-attribute group decision-making (MAGDM) problem is developed, namely for the selection of investment projects. The objective of the investment project selection problem is to choose the best project among the set of projects, seeking investment, or to rank all projects in descending order. The project selection is made considering a set of weighted attributes. To evaluate the attributes in our approach, expert assessments are used. In the proposed methodology, lingual expressions (linguistic terms) given by all experts are used as initial attribute evaluations since they are the most natural and convenient representation of experts' evaluations. Then lingual evaluations are converted into trapezoidal fuzzy numbers, and the aggregate trapezoidal hesitant fuzzy decision matrix will be built. The case is considered when information on the attribute weights is completely unknown. The attribute weights are identified based on the De Luca and Termini information entropy concept, determined in the context of hesitant fuzzy sets. The decisions are made using the extended Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method under a hesitant fuzzy environment. Hence, a methodology is based on a trapezoidal valued hesitant fuzzy TOPSIS decision-making model with entropy weights. The ranking of alternatives is performed by the proximity of their distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). For this purpose, the weighted hesitant Hamming distance is used. An example of investment decision-making is shown that clearly explains the procedure of the proposed methodology.

Procedia PDF Downloads 115

Authors: Sanjeev Kumar Appicharla

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This paper presents the results of the modelling and analysis of the European Railway Traffic Management (ERTMS) safety-critical incident to raise awareness of biases in the systems engineering process on the Cambrian Railway in the UK using the RAIB 17/2019 as a primary input. The RAIB, the UK independent accident investigator, published the Report- RAIB 17/2019 giving the details of their investigation of the focal event in the form of immediate cause, causal factors, and underlying factors and recommendations to prevent a repeat of the safety-critical incident on the Cambrian Line. The Systems for Investigation of Railway Interfaces (SIRI) is the methodology used to model and analyze the safety-critical incident. The SIRI methodology uses the Swiss Cheese Model to model the incident and identify latent failure conditions (potentially less than adequate conditions) by means of the management oversight and risk tree technique. The benefits of the systems for investigation of railway interfaces methodology (SIRI) are threefold: first is that it incorporates the “Heuristics and Biases” approach advanced by 2002 Nobel laureate in Economic Sciences, Prof Daniel Kahneman, in the management oversight and risk tree technique to identify systematic errors. Civil engineering and programme management railway professionals are aware of the role “optimism bias” plays in programme cost overruns and are aware of bow tie (fault and event tree) model-based safety risk modelling techniques. However, the role of systematic errors due to “Heuristics and Biases” is not appreciated as yet. This overcomes the problems of omission of human and organizational factors from accident analysis. Second, the scope of the investigation includes all levels of the socio-technical system, including government, regulatory, railway safety bodies, duty holders, signaling firms and transport planners, and front-line staff such that lessons are learned at the decision making and implementation level as well. Third, the author’s past accident case studies are supplemented with research pieces of evidence drawn from the practitioner's and academic researchers’ publications as well. This is to discuss the role of system thinking to improve the decision-making and risk management processes and practices in the IEC 15288 systems engineering standard and in the industrial context such as the GB railways and artificial intelligence (AI) contexts as well.

Keywords: accident analysis, AI algorithm internal audit, bounded rationality, Byzantine failures, heuristics and biases approach

Procedia PDF Downloads 188

Authors: K. Suresh, R. Arunkumar

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The objective of this study is to investigate the preparation of gramine nano suspension and protective effect of Gramine on the apoptosis of laryngeal cancer cells cell line (HEp-2 and KB). The growth inhibition rate of Hep-2 and KB cells in vitro were measured by MTT assay and apoptosis by, levels of reactive oxygen species, mitochondrial membrane potential, morphological changes and flowcytometry. Based on the results, we determined the effective doses of gramine as 127.23µm/ml for 24 hr and 119.81 µm/ml for 48hr in hep-2 cell line and 147.58 µm ml for 24 hr and 123.74µm µm/ml for 48hr in KB cell line. cytotoxicity effects of gramine were confirmed by treatment of HEp-2 cell and KB cell with IC50 concentration of gramine resulted in sequences of events marked by the enhance the apoptosis accompanied by loss of cell viability, modulation of reactive oxygen species and cell cycle arrest through the induction of G0/G1 phase arrest on HEp-2 cells. Our study suggests that the nanosuspension of gramine possesses the more cytotoxic effect of cancer cells and a novel candidate for cancer chemoprevention.

Keywords: apoptosis, HEp-2 cell line, KB cell line mitochondria, gramine, nanosuspension

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Authors: Ribeiro Tiago Magalhães

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Objective: The objective of this study was to evaluate the influence of a hydroelectric power plant in the state of Amapá, and to present the results obtained by dimensioning the diversity of the main mosquito vectors involved in the transmission of pathogens that cause diseases such as malaria, dengue and leishmaniasis. Methodology: The present study was conducted on the banks of the Araguari River, in the municipalities of Porto Grande and Ferreira Gomes in the southern region of Amapá State. Nine monitoring campaigns were conducted, the first in April 2014 and the last in March 2016. The selection of the catch sites was done in order to prioritize areas with possible occurrence of the species considered of greater importance for public health and areas of contact between the wild environment and humans. Sampling efforts aimed to identify the local vector fauna and to relate it to the transmission of diseases. In this way, three phases of collection were established, covering the schedules of greater hematophageal activity. Sampling was carried out using Shannon Shack and CDC types of light traps and by means of specimen collection with the hold method. This procedure was carried out during the morning (between 08:00 and 11:00), afternoon-twilight (between 15:30 and 18:30) and night (between 18:30 and 22:00). In the specific methodology of capture with the use of the CDC equipment, the delimited times were from 18:00 until 06:00 the following day. Results: A total of 32 species of mosquitoes was identified, and a total of 2,962 specimens was taxonomically subdivided into three genera (Culicidae, Psychodidae and Simuliidae) Psorophora, Sabethes, Simulium, Uranotaenia and Wyeomyia), besides those represented by the family Psychodidae that due to the morphological complexities, allows the safe identification (without the method of diaphanization and assembly of slides for microscopy), only at the taxonomic level of subfamily (Phlebotominae). Conclusion: The nine monitoring campaigns carried out provided the basis for the design of the possible epidemiological structure in the areas of influence of the Cachoeira Caldeirão HPP, in order to point out among the points established for sampling, which would represent greater possibilities, according to the group of identified mosquitoes, of disease acquisition. However, what should be mainly considered, are the future events arising from reservoir filling. This argument is based on the fact that the reproductive success of Culicidae is intrinsically related to the aquatic environment for the development of its larvae until adulthood. From the moment that the water mirror is expanded in new environments for the formation of the reservoir, a modification in the process of development and hatching of the eggs deposited in the substrate can occur, causing a sudden explosion in the abundance of some genera, in special Anopheles, which holds preferences for denser forest environments, close to the water portions.

Keywords: Amazon, hydroelectric, power, plants

Procedia PDF Downloads 191

Authors: Rizwan H. Khan, Saima Nusrat

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Despite the fact that amyloid associated neurodegenerative diseases and non-neuropathic systemic amyloidosis have allured the research endeavors, as no curative drugs have been proclaimed up till now except for symptomatic cure. Therapeutic compounds which can diminish or disaggregate such toxic oligomers and fibrillar species have been examined and more are on its way. In the present study, we had reported an extensive biophysical, microscopic and computational study, revealing that L-3, 4-dihydroxyphenylalanine (L-Dopa) possess undeniable potency to inhibit heat induced human lysozyme (HL) amyloid fibrillation and also retain the fibril disaggregating potential. L-Dopa interferes in the amyloid fibrillogenesis process by interacting hydrophobically and also by forming hydrogen bonds with the amino acid residues found in amyloid fibril forming prone region of HL as elucidated by molecular docking results. L-Dopa also disaggregates the mature amyloid fibrils into some unorganised species. Thus, L-Dopa and related compounds can work as a promising inhibitor for the therapeutic advancement prospective against systemic amyloidosis.

Keywords: amyloids, disaggregation, human lysozyme, molecular docking

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Moncer Malika, Ben Brahim Mounir, Bel Hassen Malika, Hamza Asma

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During the last decades, microalgae communities have presented significant changes in their structure and taxa composition along the Mediterranean littoral shallow waters. The main purpose of this work was to evaluate possible changes, over a 17-year scale (1997–2013), in the diversity and abundance of three toxic and potentially toxic microalgae related to changes in environmental parameters on Sfax coasts, a pole of shellfish production in Tunisia. In this 17-year span, a chronological series of data showed that a clear disparity from one year to another was observed in the abundance of studied species. The distribution of these species has been subjected to a seasonal cycle. The studied microalgae, especially Prorocentrum lima, seem to have significant relationships with many physicochemicaland meteorological parameters.

Keywords: long-term monitoring HABs, physico-chemical parameters, meteorological parameters, Prorocentrum lima, Ostreopsis cf. ovata, Coolia monotis

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Authors: Aisha Liaquat Ali, Ghulam Sarwar Gachal, Muhammad Yusuf Sheikh

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The squirrel commonly known as ‘Gulhari’ belongs to the order Rodentia, family sciuridea, its sub-species inhabit tropical to sub tropical regions of Asia. The core aim of the present study is to investigate the taxonomy of squirrel in District Jamshoro. Sampling was obtained for the taxonomic identification from various adjoining areas of District Jamshoro by non random method. During present study a total number of 107 specimens were collected from July 2018 to December 2018, specimens were collected from District Jamshoro it was observed that the prevalence of the sub-species Funambulus tristriatus numarius (23.3%), Funambulus pennant tulescens (23.3%) was high while Funambulus tristriatus tristriatus ((20.5%), Funambulus palmarun brodie (18.6%) and the minimum prevalence Funambulus palmaruns palmaruns (14.1%). In the present research, it is established that the climate factors, altitude has principal importance in the poor density of squirrel.

Keywords: Jamshoro District Pakistan, squirrel, taxonomy, prevalence

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Authors: Eng. M. Ahmed, A. Ibrahim, M. Ashour

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One of the major concerns facing dam is the repair of their structures to prevent the seepage under them. In previous years, many existing dams have been treated by grouting, but with varying degrees of success. One of the major reasons for this erratic performance is the unsuitable selection of the grouting materials to reduce the seepage. Grouting is an effective way to improve the engineering properties of the soil and strengthen of the permeability of the soil to reduce the seepage. The purpose of this paper is to focus on the efficiency of current available grouting materials and techniques from construction, environmental and economical point of view. The seepage reduction usually accomplished by either chemical grouting or cementious grouting using ultrafine cement. In addition, the study shows a comparison between grouting materials according to their degree of permeability reduction and cost. The application of seepage reduction is based on the permeation grouting using grout curtain installation. The computer program (SEEP/W) is employed to model a dam rested on sandy soil, using grout curtain to reduce seepage quantity and hydraulic gradient by different grouting materials. This study presents a relationship that takes into account the permeability of the soil, grout curtain spacing and a new performance parameter that can be used to predict the best selection of grouting materials for seepage reduction.

Keywords: seepage, sandy soil, grouting, permeability

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Authors: Lawan Muhammad Adam, Abduljabar Hilal Alsayoud

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One of the most promising techniques to produce pure hydrogen is through a palladium-based membrane (Pd-membrane). Density functional theory (DFT) is employed in this work to examine how the physical and chemical adsorption properties of hydrogen on the surface of Pd-Pt can be mutated in the presence of contaminating gases, CH₄, CO, and CO₂. The main target is to survey the energy topology related to hydrogen adsorption while adjusting the stages of freedom in both the structure and composition. The adsorption sites, crystal plane of the slab, and relative orientation of the adsorbed molecules on its surface, as well as various arrangements of adsorbed species, have been considered in this study. The dependency of hydrogen adsorption on surface coverage is studied. The study demonstrated the physical adsorption energies of the molecules on the surface concerning the different coverages of hydrogen atoms. The most stable combinations of the adsorption sites (Top, Hollow, and Bridge) with various orientations of gaseous molecules on the Pd-Pt surface were identified according to their calculated energies. When the binding of contaminating gaseous species to the Pd-Pt surface and their impact on the physical adsorption energies of the H₂ are examined, it is observed that the most poisonous gas relative to all other gases modifies the energetics of the adsorption process of hydrogen on the surface.

Keywords: DFT, Pd-Pt-membrane, H₂, CO, CO₂

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Authors: Aisha Liaquat Ali, Ghulam Sarwar Gachal, Muhammad Yusuf Sheikh

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The Parrot rose ringed (Psittaculla krameri) commonly known as Tota, belongs to the order ‘Psittaciformes’ and family ‘Psittacidea’. Its sub-species inhabiting Pakistan are Psittaculla borealis. The parrot rose-ringed has been categorized the least concern species, the core aim of the present study is to investigate the ecology and taxonomy of parrot (rose-ringed). Sampling was obtained for the taxonomic identification from various adjoining areas in City Mirpurkhas by non-random method, which was conducted from Feb to June 2017. The different parameters measured with the help of a vernier caliper, foot scale, digital weighing machine. Body parameters were measured via; length of body, length of the wings, length of tail, mass in grams. During present study, a total number of 36 specimens were collected from different localities of City Mirpurkhas (38.2%) were male and (62.7%) were female. Maximum population density of Psittaculla Krameri borealis (52.9%) was collected from Sindh Horticulture Research Station (fruit farm) Mirpurkhas. Minimum no: of Psittaculla krameri borealis (5.5%) collected in urban parks. It was observed that Psittaculla krameri borealis were in dense population during the months of ‘May’ and ‘June’ when the temperature ranged between 20°C and 45°C. A Psittaculla krameri borealis female was found the heaviest in body weight. The species of parrot (rose ringed) captured during study having green plumage, coverts were gray, upper beak, red and lower beak black, shorter tail in female long tail in the male which was similar to the Psittaculla krameri borealis.

Keywords: Mirpurkhas Sindh Pakistan, environmental ecology, parrot, rose-ringed, taxonomy

Procedia PDF Downloads 173

Authors: Sayyed Benyamin Alavi, Giovanni Cerri, Leila Chennaoui, Ambra Giovannelli, Stefano Mazzoni

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Primary energy consumption and emissions of pollutants (including CO2) sustainability call to search methodologies to lower power absorption for unit of a given product. Cool production plants based on vapour compression are widely used for many applications: air conditioning, food conservation, domestic refrigerators and freezers, special industrial processes, etc. In the field of cool production, the amount of Yearly Consumed Primary Energy is enormous, thus, saving some percentage of it, leads to big worldwide impact in the energy consumption and related energy sustainability. Among various techniques to reduce power required by a Vapour Compression Cool Production Plant (VCCPP), the technique based on Power Regeneration by means of Internal Direct Cycle (IDC) will be considered in this paper. Power produced by IDC reduces power need for unit of produced Cool Power by the VCCPP. The paper contains basic concepts that lead to develop IDCs and the proposed options to use the IDC Power. Among various selections for using turbo machines, Best Economically Available Technologies (BEATs) have been explored. Based on vehicle engine turbochargers, they have been taken into consideration for this application. According to BEAT Database and similarity rules, the best turbo machine selection leads to the minimum nominal power required by VCCPP Main Compressor. Results obtained installing the prototype in “ad hoc” designed test bench will be discussed and compared with the expected performance. Forecasts for the upgrading VCCPP, various applications will be given and discussed. 4-6% saving is expected for air conditioning cooling plants and 15-22% is expected for cryogenic plants.

Keywords: Refrigeration Plant, Vapour Pressure Amplifier, Compressor, Expander, Turbine, Turbomachinery Selection, Power Saving

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Authors: Imed Feki, Faouzi Msahli

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Selection of relevant parameters from a high dimensional process operation setting space is a problem frequently encountered in industrial process modelling. This paper presents a method for selecting the most relevant fabric physical parameters for each sensory quality feature. The proposed relevancy criterion has been developed using two approaches. The first utilizes a fuzzy sensitivity criterion by exploiting from experimental data the relationship between physical parameters and all the sensory quality features for each evaluator. Next an OWA aggregation procedure is applied to aggregate the ranking lists provided by different evaluators. In the second approach, another panel of experts provides their ranking lists of physical features according to their professional knowledge. Also by applying OWA and a fuzzy aggregation model, the data sensitivity-based ranking list and the knowledge-based ranking list are combined using our proposed percolation technique, to determine the final ranking list. The key issue of the proposed percolation technique is to filter automatically and objectively the relevant features by creating a gap between scores of relevant and irrelevant parameters. It permits to automatically generate threshold that can effectively reduce human subjectivity and arbitrariness when manually choosing thresholds. For a specific sensory descriptor, the threshold is defined systematically by iteratively aggregating (n times) the ranking lists generated by OWA and fuzzy models, according to a specific algorithm. Having applied the percolation technique on a real example, of a well known finished textile product especially the stonewashed denims, usually considered as the most important quality criteria in jeans’ evaluation, we separate the relevant physical features from irrelevant ones for each sensory descriptor. The originality and performance of the proposed relevant feature selection method can be shown by the variability in the number of physical features in the set of selected relevant parameters. Instead of selecting identical numbers of features with a predefined threshold, the proposed method can be adapted to the specific natures of the complex relations between sensory descriptors and physical features, in order to propose lists of relevant features of different sizes for different descriptors. In order to obtain more reliable results for selection of relevant physical features, the percolation technique has been applied for combining the fuzzy global relevancy and OWA global relevancy criteria in order to clearly distinguish scores of the relevant physical features from those of irrelevant ones.

Keywords: data sensitivity, feature selection, fuzzy logic, OWA operators, percolation technique

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Authors: Piotr Ciuman, Barbara Lipska

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The aim of presented research was to improve numerical predictions of air parameters distribution in the actual natatorium by the selection of calculation formula of mass flux of moisture emitted from the pool. Selected correlation should ensure the best compliance of numerical results with the measurements' results of these parameters in the facility. The numerical model of the natatorium was developed, for which boundary conditions were prepared on the basis of measurements' results carried out in the actual facility. Numerical calculations were carried out with the use of ANSYS CFX software, with six formulas being implemented, which in various ways made the moisture emission dependent on water surface temperature and air parameters in the natatorium. The results of calculations with the use of these formulas were compared for air parameters' distributions: Specific humidity, velocity and temperature in the facility. For the selection of the best formula, numerical results of these parameters in occupied zone were validated by comparison with the measurements' results carried out at selected points of this zone.

Keywords: experimental validation, indoor swimming pool, moisture emission, natatorium, numerical calculations CFD, thermal and humidity conditions, ventilation

Procedia PDF Downloads 408

Authors: L. Abubakar, B. M. Sokoto, I. U. Mohammed, M. S. Na’allah, A. Mohammad, A. N. Garba, T. S. Bubuche

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Onion (Allium cepa var. cepa L.) is the most important species of the Allium group belonging to family Alliaceae and genus Allium. It can be regarded as the single important vegetable species in the world after tomatoes. Despite the similarities, which bring the species together, the genus is a strikingly diverse one, with more than five hundred species, which are perennial and mostly bulbous plants. Out of these, only seven species are in cultivation, and five are the most important species of the cultivated Allium. However, Allium cepa (onion) and Allium sativum (Garlic) are the two major cultivated species grown all over the world of which the onion crop is the most important. North Western Nigeria (Sokoto, Kebbi and Zamfara States) constitute the major onion producing zone in Nigeria, which is primarily during the dry season. However, onion production in the zone is seriously affected by two main factors i.e. diseases and storage losses, in addition to other constraints that limits the cultivation of the crop during the rainy season which include lack of prolonged rainy season to allow for proper maturation of the crop. The major onion disease in this zone is purple blotch caused by a fungus Alternaria porri and currently efforts are on to develop onion hybrids resistant to the disease. Genetic diversity plays an important role in plant breeding either to exploit heterosis or to generate productive recombinants. Assessment of a large number of genotypes for a genetic diversity is the first step in this direction. The objective of this research therefore is to evaluate the genetic potentials of the onion cultivars of North Western Nigeria, with a view of developing new cultivars that address the major production challenges to onion cultivation in North Western, Nigeria. Thirteen onion cultivars were collected during an expedition covering North western Nigeria and Southern part of Niger Republic during 2013, which are areas noted for onion production. The cultivars were evaluated at two locations; Sokoto, in Sokoto State and Jega in Kebbi State all in Nigeria during the 2013/14 onion season (dry season) under irrigation. The objective of the research was to determine the genetic potentials of onion cultivars of north western Nigeria as a basis for breeding purposes. Combined analysis of the results revealed highly significant variation between the cultivars across the locations with respect to plant height, number of leaves/plant, bolting %, bulb height, bulb weight, mean bulb yield and cured bulb weight, with significant variation in terms of bulb diameter. Tasa from Warra Local Government Area of Kebbi State (V4) recorded the greatest mean fresh bulb yield with Jar Albasa (V8) from Illela Local Government Area of Sokoto State recording the least. Similarly Marsa (V5) from Silame Local Government Area recorded the greatest mean cured bulb yield (marketable bulb)with Kiba (V11) from Goronyo Local Government of Sokoto State recording the least. Significant variation was recorded between the locations with respect to all characters, with Sokoto being better in terms of plant height, number of leaves/plant, bolting % and bulb diameter. Jega was better in terms of bulb height, bulb yield and cured bulb weight. Significant variation was therefore observed between the cultivars.

Keywords: evaluation, genetic, onions, North Western Nigeria

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Authors: Bachir Bentouati, Lakhdar Chaib, Saliha Chettih, Gai-Ge Wang

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The problem of economic dispatch (ED) is the basic problem of power framework, its main goal is to find the most favorable generation dispatch to generate each unit, reduce the whole power generation cost, and meet all system limitations. A heuristic algorithm, recently developed called Stud Krill Herd (SKH), has been employed in this paper to treat non-convex ED problems. The proposed KH has been modified using Stud selection and crossover (SSC) operator, to enhance the solution quality and avoid local optima. We are demonstrated SKH effects in two case study systems composed of 13-unit and 40-unit test systems to verify its performance and applicability in solving the ED problems. In the above systems, SKH can successfully obtain the best fuel generator and distribute the load requirements for the online generators. The results showed that the use of the proposed SKH method could reduce the total cost of generation and optimize the fulfillment of the load requirements.

Keywords: stud krill herd, economic dispatch, crossover, stud selection, valve-point effect

Procedia PDF Downloads 196

Authors: Irene Alevizos, Jessica Lewis, Marina Harper, John Boyce

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Acinetobacter baumannii causes a range of severe nosocomial-acquired infections, and many strains are multi-drug resistant. A. baumannii possesses survival mechanisms allowing it to thrive in competitive polymicrobial environments, including a Type VI Secretion System (T6SS) that injects effector proteins into other bacteria to give a competitive advantage. The effects of T6SS firing are broad and depend entirely on the effector that is delivered. Effects can include toxicity against prokaryotic or eukaryotic cells and the acquisition of essential nutrients. The T6SS of some species can deliver ‘specialised effectors’ that are fused directly to T6SS components, such as PAAR proteins. PAAR proteins are predicted to form the piercing tip of the T6SS and are essential for T6SS function. Although no specialised effectors have been identified in A. baumannii, many strains encode multiple PAAR proteins. Analysis of PAAR proteins across the species identified 12 families of PAAR proteins with distinct C-terminal extensions. A. baumannii AB307-0294 encodes two PAAR proteins, one of which has a C-terminal extension. Mutation of one or both of the PAAR-encoding genes in this strain showed that expression of either PAAR protein was sufficient for T6SS function. We employed a heterologous expression approach and determined that PAAR proteins from different A. baumannii strains, as well as the closely related A. baylyi species, could complement the A. baumannii ∆paar mutant and restore T6SS function. Furthermore, we showed that PAAR fusions could be used to deliver artificially cloned protein fragments by generating Histidine- and Streptavidin- tagged PAAR specialised effectors, which restored T6SS activity. This provides evidence that the fusion of protein fragments onto PAAR proteins in A. baumannii is compatible with a functional T6SS. Successful delivery by this mechanism extends the scope of what the T6SS can deliver, including user designed proteins.

Keywords: A. baumannii, effectors, PAAR, T6SS

Procedia PDF Downloads 93

Authors: Gabriel A. Juma, Adiel M. Magana, Githaiga N. Michael, James G. Kairo

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Seagrass meadows are important carbon sinks, thus understanding this role and their conservation provides opportunities for their applications in climate change mitigation and adaptation. This study aimed at understanding seagrass contribution to ecosystem carbon at Gazi Bay; by comparing carbon stocks in seagrass beds of two mangroves fringed creeks of the bay. Specifically, the objectives included assessing the distribution and abundance of seagrass in the fringed creeks, and estimating above and below-ground biomass. Results obtained would be added to the mangrove and open bay carbon in estimating total ecosystem carbon of Gazi bay. The stratified random sampling strategy was applied in this study. Transects were laid perpendicular to the waterline at intervals of 50 meters from the upper region near the mangroves to the deeper end of the creek across seagrass meadows. Along these transects, 0.25m2 square quadrats were laid at 10 m to assess distribution and composition of seagrasses in the creeks. A total of 80 plots were sampled. Above-ground biomass was sampled by harvesting all the seagrass materials within the quadrat while four sediment cores were obtained from each quarter of the quadrat and then sorted into necromass, rhizomes and roots to determine below ground biomass. Samples were cleaned and dried in the oven for 72 hours at 60˚C in the laboratory. Total biomass was determined by multiplying biomass with carbon conversion factor of 0.34. In all the statistical tests, a significant level was set at α = 0.05. Eight species of seagrass were encountered in Western creek (WC) while seven in the Eastern creek (EC). Based on importance value, the dominant species in WC were Cymodocea rotundata and Halodule uninervis while Thalassodendron ciliatum and Enhalus acoroides dominated the eastern creek. The cover of seagrass in EC was 67.97% compared to 56.45% in WC. There was a significance difference in abundance of seagrass species between the two creeks (t = 1.97, D.F = 35, p < 0.05). Similarly, there was significance differences between total seagrass biomass (t= -8.44, D.F. = 53, p < 0.05) and species composition (F(7,79) = 14.6, p < 0.05) in the two creeks. Mean seagrass in the creeks was 7.25 ± 4.2 Mg C ha-1, (range: 4.1 - 12.9 Mg C ha-1). The findings of the current study reveal variations in biomass stocks of the two creeks of Gazi bay that have varying biophysical features. It is established that habitat heterogeneity between the creeks contributes to the variation in seagrass abundance and biomass stocking. This enhances understanding of these ecosystems hence the establishment of carbon offset project in seagrass for livelihood improvement and increased conservation.

Keywords: seagrass, above-ground, below-ground, creeks, Gazi bay

Procedia PDF Downloads 129

Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

Procedia PDF Downloads 72

Authors: Nishtha, Richa, Anju Rao

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Plants are the source of herbal medicine and medicinal value of the plants lies in the bioactive phytochemical constituents that produce definite physiological effects on human body. Angiospermic families are known to produce such phytochemical constituents which are termed as secondary plant metabolites. These metabolites include alkaloids, saponins, phenolic compounds, flavonoids, tannins, terpenoids and so on. Solanaceae is one of the important families of Angiosperms known for medicinally important alkaloids such as hyoscyamine, scopolamine, solanine, nicotine, capsaicin etc. Medicinally important species of this family mostly belong to the genera of Datura,Atropa,Solanum,Withania and Nicotiana.Six species such as Datura metel, Solanum torvum, Physalis minima, Cestrum nocturnum, Cestrum diurnum and Nicotiana plumbaginifolia have been collected from different localities of Chandigarh and adjoining areas.Field and anatomical studies helped to identify the plants and their parts used for the study of secondary plant metabolites. Preliminary phytochemcial studies have been done on various parts of plants such as roots, stem and leaves by making aqueous and alcoholic extracts from their powdered forms which showed the presence of alkaloids in almost all the species followed by steroids, flavonoids, terpenoids, tannins etc. HPLC profiles of leaves of Datura metel showed the presence of active compounds such as scopalamine and hyoscyamine and Solanum torvum showed the presence of solanine and solasodine. These alkaloids are important source of drug based medicine used in pharmacognosy. The respective compounds help in treating vomiting, nausea, respiratory disorders, dizziness, asthma and many heart problems.

Keywords: alkaloids, flavanoids, phytochemical constituents, pharmacognosy, secondary metabolites

Procedia PDF Downloads 445