Search results for: tropical deciduous forest

Authors: Iacopo Carnacina, Mohammad Keshtpoor, Richard Yablonsky

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Non-structural protection measures against flooding are becoming increasingly popular flood risk mitigation strategies. In particular, coastal flood insurance impacts not only private citizens but also insurance and reinsurance companies, who may require it to retain solvency and better understand the risks they face from a catastrophic coastal flood event. In this context, a framework is presented here to assess the risk for coastal flooding across the UK. The area has a long history of catastrophic flood events, including the Great Flood of 1953 and the 2013 Cyclone Xaver storm, both of which led to significant loss of life and property. The current framework will leverage a technology based on a hydrodynamic model (Delft3D Flexible Mesh). This flexible mesh technology, coupled with a calibration technique, allows for better utilisation of computational resources, leading to higher resolution and more detailed results. The generation of a stochastic set of extra tropical cyclone (ETC) events supports the evaluation of the financial losses for the whole area, also accounting for correlations between different locations in different scenarios. Finally, the solution shows a detailed analysis for the Thames River, leveraging the information available on flood barriers and levees. Two realistic disaster scenarios for the Greater London area are simulated: In the first scenario, the storm surge intensity is not high enough to fail London’s flood defences, but in the second scenario, London’s flood defences fail, highlighting the potential losses from a catastrophic coastal flood event.

Keywords: storm surge, stochastic model, levee failure, Thames River

Procedia PDF Downloads 232

Authors: Mercy Chepkirui, Paul Orina, Priscilla Boera, Judith Achoki

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Oreochromis jipe is a tropical freshwater bentho-pelagic fish belonging to the Cichlid family that is endemic to the Pangani River basin and Lake Jipe in Kenya and northern Tanzania, while Oreochromis niloticus inhabits the Lake Victoria basin with reported cases in Lake jipe too. Unlike O. jipe, Oreochromis niloticus is spreading across the globe due to its cultural potential. This, however, could cause genetic purity concerns in the event of cross-breeding among the tilapiines, which is already taking place in the wild. The study envisaged establishing the possibility of hybridization among the two species under aquaculture conditions and phenotypically informing the difference between pure and cross lines. Two hundred sixteen mature brooders weighing 100-120g were selected randomly, 108 of Oreochromis Jipe and 108 of Oreochromis niloticus; for each trial, 72 males and 144 females were distributed into 3 crosses, each grouped in triplicates (Oreochromis niloticus (♀) X Oreochromis niloticus(♂);Oreochromis niloticus (♂) X Oreochromis jipe ( ♀); Oreochromis jipe (♂) X Oreochromis niloticus (♀); Oreochromis jipe (♂) X Oreochromis jipe (♀). All trials had the F1 generation, which is currently undergoing growth trials and assessing its viability for the 2nd generation. The results indicated that Oreochromis niloticus has better growth, followed by crosses (Oreochromis niloticus X Oreochromis jipe) and, finally, pure line Oreochromis jipe. Further, pure Oreochromis jipe F1 demonstrated potential for aquaculture adoption despite its recent introduction into aquaculture; thus, this will help towards the conservation of indigenous fish species of Lake Jipe fishery, which is currently under the Internationa Union for Conservation of Nature Red List of endangered fish species. However, there is a need to inform the purity of existing Oreochromis jipe wild stocks to inform genetic material conservation.

Keywords: biodiversity, climate change, fisheries, oreochromis jipe, conservation

Procedia PDF Downloads 128

Authors: Isa Muhammad Zumo

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The African Great Green Wall (GGW) is a significant initiative in northern Nigeria because it promotes land restoration and conservation utilizing both commercial and species of forest trees while also helping to mitigate desertification and hazards from the sand dunes and shifting Sahara deserts. Conflicts and weather, however, pose a significant danger to the achievement of these goals. The scientific method for monitoring the vegetation dynamics since inception has not received the required attention, despite the African Development Bank (ADB)'s help in funding the project and its integration into the state's development plans for GGW initiatives. This study will monitor the changes in the vegetation cover of the great green wall within Yobe State Nigeria from 2014 to 2023. The vegetation dynamics will be monitored using Landsat 8 Operational Land Imager (OLI) for 6 years at 2 years intervals. The result will show the fluctuations in the vegetation cover density within the period of study. This will guide the design and implementation of policies of the GGW in achieving its objectives. The result can also contribute to the realization of Sustainable Development Goal (SDG) Target 13.2: Integrate climate change measures into national policies, strategies, and planning.

Keywords: monitoring, green wall, Landsat 8, Nigeria

Procedia PDF Downloads 87

Authors: Mohammed Bnebaghdad, Feriel Betouche, Malika Semmani

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Image processing become more sophisticated over time due to technological advances, especially artificial intelligence (AI) technology. Currently, AI image processing is used in many areas, including surveillance, industry, science, and medicine. AI in medical image processing can help doctors diagnose diseases faster, with minimal mistakes, and with less effort. Among these diseases is malaria, which remains a major public health challenge in many parts of the world. It affects millions of people every year, particularly in tropical and subtropical regions. Early detection of malaria is essential to prevent serious complications and reduce the burden of the disease. In this paper, we propose and implement a scheme based on AI image processing to enhance malaria disease diagnosis through automated analysis of blood smear images. The scheme is based on the convolutional neural network (CNN) method. So, we have developed a model that classifies infected and uninfected single red cells using images available on Kaggle, as well as real blood smear images obtained from the Central Laboratory of Medical Biology EHS Laadi Flici (formerly El Kettar) in Algeria. The real images were segmented into individual cells using the watershed algorithm in order to match the images from the Kaagle dataset. The model was trained and tested, achieving an accuracy of 99% and 97% accuracy for new real images. This validates that the model performs well with new real images, although with slightly lower accuracy. Additionally, the model has been embedded in a Raspberry Pi4, and a graphical user interface (GUI) was developed to visualize the malaria diagnostic results and facilitate user interaction.

Keywords: medical image processing, malaria parasite, classification, CNN, artificial intelligence

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Authors: Zhang Hui, Wu Caiqiu, Yuan Xuyin, Qiu Jie, Zhang Hanpei

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The heavy metal contaminations were determined with a detailed soil survey in roadside soils along Shenyang-Dalian Highway of Liaoning Province (China) and Pb, Cu, Cd, Ni and Zn were analyzed using the atomic absorption spectrophotometric method. The average concentration of Pb, Cu, Cd, Ni and Zn in roadside soils was determined to be 43.8, 26.5, 0.119, 32.1, 71.3 mg/kg respectively, and all of the heavy metal contents were higher than the background values. Different heavy metal distribution regularity was found in different land use type of roadside soil, there was an obvious peak of heavy concentration at 25m from road edge in the farmland, while in the forest and orchard soil, all heavy metals gradually decreased with the increase of distance from road edge and conformed to the exponential model. Furthermore, the heavy metal contents of heavy metals except Cd were markedly increased compared with those in 1999 and 2007, and the heavy metals concentrations of Shenyang- Dalian Highway were considered medium or low in comparison with those in other cities around the world. The assessment of heavy metal contamination of roadside soils illustrated a common low pollution for all heavy metal and recommended that more attention should be paid to Pb contamination in roadside soils in Shenyang-Dalian Highway.

Keywords: heavy metal contamination, roadside, highway, Nemerow Pollution Index

Procedia PDF Downloads 267

Authors: Prashant Verma

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Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling

Procedia PDF Downloads 144

Authors: Mário Ernesto Sitoe, Orlando Zacarias

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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

Procedia PDF Downloads 84

Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Diego Cruz, Helbert Arevalo, Diana Vernot

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In 2013, the Food and Agriculture Organization of the United Nations (FAO) said that insect production for food and feed could become an economic opportunity for rural women in developing countries. However, since then, just a few initiatives worldwide had tried to implement this kind of project in zones of tropical countries without previous experience in cricket production and insect human consumption, such as Colombia. In this project, ArthroFood company and the University of La Sabana join efforts to make a holistic multi-perspective analysis from biological, economic, culinary, and social sides of the Gryllodes sigillatus production by rural women of the municipality of La Mesa, Cundinamarca, Colombia. From a biological and economic perspective, G. sigillatus production in a 60m2 greenhouse was evaluated considering the effect of rearing density and substrates on final weight and length, developing time, survival rate, and proximate composition. Additionally, the production cost and labor hours were recorded for five months. On the other hand, from a socio- economic side, the intention of the rural women to implement cricket farms or micro-entrepreneurship around insect production was evaluated after developing ethnographies and empowerment, entrepreneurship, and cricket production workshops. Finally, the results of the elaboration of culinary recipes with cricket powder incorporating cultural aspects of the context of La Mesa, Cundinamarca, will be presented. This project represents Colombia's first attempt to create a social business model of cricket production involving rural women, academies, the private sector, and local authorities.

Keywords: cricket production, developing country, edible insects, entrepreneurship, insect culinary recipes

Procedia PDF Downloads 106

Authors: Budoor Al Abid

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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

Procedia PDF Downloads 197

Authors: Aldrin R. Logdat

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The insights and wisdom of the Alangan Mangyans offer valuable guidance for developing alternative ecological and development frameworks. Their reverence for the sacredness of the land, rooted in their traditional cosmology, guides their harmonious relationship with nature. Through their practice of swidden farming, ecosystem preservation takes precedence as they carefully manage agricultural activities and allow for forest regeneration. This approach aligns with natural processes, reflecting their profound understanding of the natural world. Similar to early advocates like Aldo Leopold, the emphasis is on shifting our perception of land from a commodity to a community. The indigenous wisdom of the Alangan Mangyans provides practical and sustainable approaches to preserving the interdependence of the biotic community and ecosystems. By integrating their cultural heritage, we can transcend the prevailing anthropocentric mindset and foster a meaningful and sustainable connection with nature. The revitalization of cultural energy and the embrace of alternative frameworks require learning from indigenous peoples like the Alangan Mangyans, where reverence for the land and the recognition of the interconnectedness between humanity and nature are prioritized. This paves the way for a future where harmony with nature and the well-being of the Earth community prevail.

Keywords: Alangan Mangyans, ecological frameworks, sacredness of the land, cultural energy

Procedia PDF Downloads 106

Authors: Raahil Sheikh, Abhishek Maurya, Priya Gujjar, Himanshu Dwivedi, Prathamesh Minde

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UAVs have been an initial member of our environment since it's the first used by Austrian warfare in Venice. At that stage, they were just pilotless balloons equipped with bombs to be dropped on enemy territory. Over time, technological advancements allowed UAVs to be controlled remotely or autonomously. This study shall mainly focus on the intensification of pre-existing manual drones equipping them with a variety of sensors and making them autonomous, and capable, and purposing them for a variety of roles, including thermal sensing, data collection, tracking creatures, forest fires, volcano detection, hydrothermal studies, urban heat, Island measurement, and other environmental research. The system can also be used for reconnaissance, research, 3D mapping, and search and rescue missions. This study mainly focuses on automating tedious tasks and reducing human errors as much as possible, reducing deployment time, and increasing the overall efficiency, efficacy, and reliability of the UAVs. Creation of a comprehensive Ground Control System UI (GCS) enabling less trained professionals to be able to use the UAV with maximum potency. With the inclusion of such an autonomous system, artificially intelligent paths and environmental gusts and concerns can be avoided.

Keywords: UAV, drone, autonomous system, thermal imaging

Procedia PDF Downloads 75

Authors: Leila M. Carvalho, Maria Erica S. Oliveira, Arnoud C. Neto, Elza I. Ida, Massami Shimokomaki, Marta S. Madruga

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The quality of broiler breast meat is changing as a result of the continuing emphasis on genetic selection for a more efficient meat production. Breast meat has been classified as PSE (pale, soft, exudative), DFD (dark, firm, dry) and normal color meat, and recently a third group has emerged: the so-called PFN (pale, firm, non-exudative) meat. This classification was based on pH, color and functional properties. The aim of this work was to confirm the existence of PFN and PSE meat by biochemical characterization and functional properties. Twenty four hours of refrigerated fillet, Pectoralis major, m. samples (n= 838) were taken from Cobb flocks 42-48 days old, obtained in Northeastern Brazil tropical region, the Northeastern, considered to have only dry and wet seasons. Color (L*), pH, water holding capacity (WHC), values were evaluated and compared with PSE group samples. These samples were classified as Normal (465.8), PSE meat (L*≥53; pH<5.8) and PFN (L*≥53; pH>5.8). The occurrence of control meat, PSE and PFN was 69.09%, 11.10% and 19.81%, respectively. Samples from PFN presented 4.0-5.0% higher WHC in relation to PSE meat and similar to control group. These results are explained by the fact that PSE meat syndrome occurs because of higher protein denaturation as the consequence of a simultaneous lower pH values under warm carcass sooner after slaughtering impairing the myofibril proteins functional properties. Conversely, PFN samples follow normal glycolysis rate maintaining the normal proteins activities. In conclusion, the results reported herein confirm the existence of this emerging broiler meat group with similar properties as control group and it should be considered as normal breast meat group.

Keywords: broiler breast meat, funcional properties, PFN, PSE

Procedia PDF Downloads 249

Authors: Raahil Sheikh, Prathamesh Minde, Priya Gujjar, Himanshu Dwivedi, Abhishek Maurya

Abstract:

UAVs have been an initial member of our environment since it's the first used by Austrian warfare in Venice. At that stage, they were just pilotless balloons equipped with bombs to be dropped on enemy territory. Over time, technological advancements allowed UAVs to be controlled remotely or autonomously. This study shall mainly focus on the intensification of pre-existing manual drones equipping them with a variety of sensors and making them autonomous, and capable, and purposing them for a variety of roles, including thermal sensing, data collection, tracking creatures, forest fires, volcano detection, hydrothermal studies, urban heat, Island measurement, and other environmental research. The system can also be used for reconnaissance, research, 3D mapping, and search and rescue missions. This study mainly focuses on automating tedious tasks and reducing human errors as much as possible, reducing deployment time, and increasing the overall efficiency, efficacy, and reliability of the UAVs. Creation of a comprehensive Ground Control System UI (GCS) enabling less trained professionals to be able to use the UAV with maximum potency. With the inclusion of such an autonomous system, artificially intelligent paths and environmental gusts and concerns can be avoided

Keywords: UAV, autonomous systems, drones, geo thermal imaging

Procedia PDF Downloads 86

Authors: M. Irfan Fareed, Muhammad Tahir, Alvina Gul Kazi

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Castor bean (Ricinus communis; family Euphorbiaceae) is cultivated for the production of oil and as an ornamental plant throughout tropical regions. Leaf samples from castor bean plants with leaf curl and vein thickening were collected from areas around Okara (Pakistan) in 2011. PCR amplification using diagnostic primers showed the presence of a begomovirus and subsequently the specific pair (BurNF 5’- CCATGGTTGTGGCAGTTGATTGACAGATAC-3’, BurNR 5’- CCATGGATTCACGCACAGGGGAACCC-3’) was used to amplify and clone the whole genome of the virus. The complete nucleotide sequence was determined to be 2,759 nt (accession No. HE985227). Alignments showed the highest levels of nucleotide sequence identity (98.8%) with Cotton leaf curl Burewala virus (CLCuBuV; accession No. JF416947) No. JF416947). The virus in castor beans lacks on intact C2 gene, as is typical of CLCuBuV in cotton. An amplification product of ca. 1.4 kb was obtained in PCR with primers for betasatellites and the complete nucleotide sequence of a clone was determined to be 1373 nt (HE985228). The sequence showed 96.3% nucleotide sequence identity to the recombinant Cotton leaf curl Multan betasatellite (CLCuMB; JF502389). This is the first report of CLCuBuV and its betasatellite infecting castor bean, showing this plant species as an alternate host of the virus. Already many alternate host have been reported from different alternate host like tobacco, tomato, hibiscus, okra, ageratum, Digera arvensis, habiscus, Papaya and now in Ricinus communis. So, it is suggested that these alternate hosts should be avoided to grow near cotton growing regions.

Keywords: Ricinus communis, begomovirus, betasatellite, agriculture

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Authors: Mousa Keshavarz, Abdul-Reza Dabbagh, Maryam Soyuf Jahromi

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The diversity of mangrove macrobenthos assemblages at mudflat and mangrove ecosystems of Port Khamir, Iran were investigated for one year. During this period, we measured physicochemical properties of water temperature, salinity, pH, DO and the density and distribution of the macrobenthos. We sampled a total of 9 transects, at three different topographic levels along the intertidal zone at three stations. Assemblages at class level were compared. The five most diverse and abundant classes were Foraminifers (54%), Gastropods (23%), Polychaetes (10%), Bivalves (8%) & Crustaceans (5%), respectively. Overall densities were 1869 ± 424 ind/m2 (26%) in spring, 2544 ± 383 ind/m2(36%) in summer, 1482 ± 323 ind/m2 (21%) in autumn and 1207 ± 80 ind/m2 (17%) in winter. Along the intertidal zone, the overall relative density of individuals at high, intermediate, and low topographic levels was 40, 30, and 30% respectively. Biodiversity indices were used to compare different classes: Gastropoda (Shannon index: 0.33) and Foraminifera (Simpson index: 0.28) calculated the highest scores. It was also calculated other bio-indices. With the exception of bivalves, filter feeders were associated with coarser sediments at higher intertidal levels, while deposit feeders were associated with finer sediments at lower levels. Salinity was the most important factor acting on community structure, while DO and pH had little influence.

Keywords: macrobenthos, biodiversity, mangrove forest, Khamir Port

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Authors: N. Khater, S. A. Menina, H. Benbouza

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Juniperus thurefera is an endemic cupressacée constitutes a forest cover in the mountains of Aures (Algeria). It is a heritage and important ecological richness but continues to decline, highly endangered species in danger of extinction, these populations show significant originality due to climatic conditions of the environment, because of its strength and extraordinary vitality, made a powerful but fragile and unique ecosystem in which natural regeneration by seed is almost absent in Algeria. Because of the quality of seeds that are either dormant or affected at the tree and the ground level by a large number of pests and parasites, which will lead to the total disappearance of this species and consequently leading to the biodiversity. View the ecological and socio- economic interest presented by this case, it deserves to be preserved and produced in large quantities in this respect. The present work aims to try to regenerate the Juniperus thurefera via vegetative propagation. We studied the potential of cuttings to form adventitious roots and buds. Cuttings were taken from young subjects from 5 to 20 years treated with indole butyric acid (AIB) and planted out-inside perlite under atomizer whose temperature and light are controlled. Results indicated that the percentage of developing buds on cuttings is better than the rooting ones.

Keywords: Juniperus thurefera, indole butyric acid, cutting, buds, rooting

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Authors: Cherak Imen, Sellami Mehdi

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The Atlas cedar, Cedrus atlantica, is endemic to the mountains of North Africa. This is one of the most valuable softwood, both economically, ecologically, aesthetically and culturally. In Algeria, the cedar forests currently have worrying symptoms of decline which therefore require special monitoring. Fungal endophytes are involved in various diseases of the Atlas cedar. They attack all organs on which they cause many symptoms. These microflora live in complex interaction with plants. In this study, we identified a total of 09 mycotaxons collected needles Cedarwood at three stations with different degrees of decline (Talmet, Boumerzoug and Tuggurt) in the National Park Belezma (Batna, Algeria). The study conducted on a total of 12 trees were identified 08 mycoendophytes in Talmet station, 04 species in the Boumerzoug station and 03 in Tuggurt station. The total species richness mycoendophytes depending on the types of cedar forests showed that the largest diversity was recorded at the cedar forest healthy, Alternaria is the most common type in all stations. This work should be completed by further detailed studies to identify other endophyte species and better know its interactions with the Atlas cedar.

Keywords: Cedrus atlantica, endophytic fungi, microflora, mycotaxons, mycoendophyte

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Authors: Omar Ali, Adesh Ramsubhag, Jayaraj Jayaraman

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Seaweed extracts have been reported as plant biostimulants which could be a safer, organic alternative to harsh pesticides. The incentive to use seaweed-based biostimulants is becoming paramount in sustainable agriculture. The current study, therefore, screened a commercial extract of A. nodosum in tomatoes, cultivated in Trinidad to showcase the multiple beneficial effects. Foliar treatment with an A. nodosum commercial extract led to significant increases in fruit yield and a significant reduction of incidence of bacterial spots and early blight diseases under both greenhouse and field conditions. Investigations were carried out to reveal the possible mechanisms of action of this biostimulant through defense enzyme assays and transcriptome profiling via RNA sequencing of tomato. Studies into disease control mechanisms by A. nodosum showed that the extract stimulated the activity of enzymes such as peroxidase, phenylalanine ammonia-lyase, chitinase, polyphenol oxidase, and β-1,3-glucanase. Additionally, the transcriptome survey revealed the upregulation and enrichment of genes responsible for the biosynthesis of growth hormones, defense enzymes, PR proteins and defense-related secondary metabolites, as well as genes involved in the nutrient mobilization, photosynthesis and primary and secondary metabolic pathways. The results of the transcriptome study also demonstrated the cross-talks between growth and defense responses, confirming the bioelicitor and biostimulant value of seaweed extracts in plants. These effects could potentially implicate the benefits of seaweed extract and validate its usage in sustainable crop production.

Keywords: A. nodosum, biostimulants, elicitor, enzymes, growth responses, seaweeds, tomato, transcriptome analysis

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Authors: Januar Parlaungan Siregar, Davindra Brabu Mathivanan, Dandi Bachtiar, Mohd Ruzaimi Mat Rejab, Tezara Cionita

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Natural fibres play a significant role in mass industries such as automotive, construction and sports. Many researchers have found that the natural fibres are the best replacement for the synthetic fibres in terms of cost, safety, and degradability due to the shortage of landfill and ingestion of non biodegradable plastic by animals. This study mainly revolved around pineapple leaf fibre (PALF) which is available abundantly in tropical countries and with excellent mechanical properties. The composite formed in this study is highly biodegradable as both fibre and matrix are both derived from natural based products. The matrix which is polylactic acid (PLA) is made from corn starch which gives the upper hand as both material are renewable resources are easier to degrade by bacteria or enzyme. The PALF is treated with different alkaline solution to remove excessive moisture in the fibre to provide better interfacial bonding with PLA. Thereafter the PALF is washed with distilled water several times before placing in vacuum oven at 80°C for 48 hours. The dried PALF later were mixed with PLA using extrusion method using fibre in percentage of 30 by weight. The temperature for all zone were maintained at 160°C with the screw speed of 50 rpm for better bonding and afterwards the products of the mixture were pelletized using pelletizer. The pellets were placed in the specimen-sized mould for hot compression under the temperature of 170°C at 5 MPa for 5 min and subsequently were cold pressed under room temperature at 5 MPa for 5 min. The specimen were tested for tensile and flexure strength according to American Society for Testing and Materials (ASTM) D638 and D790 respectively. The effect of surface modification on PALF with different alkali solution will be investigated and compared.

Keywords: natural fibre, PALF, PLA, composite

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Authors: Anandita Mitro, Archana Srivastava, Bidisha Banerjee

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The present paper attempts to analyze the hierarchy and interconnection of factors responsible for the uptake of BCG vaccination in India. The study uses National Family Health Survey (NFHS-5) data which was conducted during 2019-21. The univariate logistic regression method is used to understand the univariate effects while the interconnection effects have been studied using the Categorical Inference Tree (CIT) which is a non-parametric Machine Learning (ML) model. The hierarchy of the factors is further established using Conditional Inference Forest which is an extension of the CIT approach. The results suggest that BCG vaccination coverage was influenced more by system-level factors and awareness than education or socio-economic status. Factors such as place of delivery, antenatal care, and postnatal care were crucial, with variations based on delivery location. Region-specific differences were also observed which could be explained by the factors. Awareness of the disease was less impactful along with the factor of wealth and urban or rural residence, although awareness did appear to substitute for inadequate ANC. Thus, from the policy point of view, it is revealed that certain subpopulations have less prevalence of vaccination which implies that there is a need for population-specific policy action to achieve a hundred percent coverage.

Keywords: vaccination, NFHS, machine learning, public health

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Authors: Rabia Munsaf Khan, Eshrat Fatima

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The analysis of the spatial extent and temporal change of vegetation cover using remotely sensed data is of critical importance to agricultural sciences. Pakistan, being an agricultural country depends on this resource as it makes 70% of the GDP. The case study is of Lal Suhanra National Park, which is not only the biggest forest reserve of Pakistan but also of Asia. The study is performed using different temporal images of Landsat. Also, the results of Landsat are cross-checked by using Sentinel-2 imagery as it has both higher spectral and spatial resolution. Vegetation can easily be detected using NDVI which is a common and widely used index. It is an important vegetation index, widely applied in research on global environmental and climatic change. The images are then classified to observe the change occurred over 15 years. Vegetation cover maps of 2000 and 2016 are used to generate the map of vegetation change detection for the respective years and to find out the changing pattern of vegetation cover. Also, the NDVI values aided in the detection of percentage decrease in vegetation cover. The study reveals that vegetation cover of the area has decreased significantly during the year 2000 and 2016.

Keywords: Landsat, normalized difference vegetation index (NDVI), sentinel 2, Greenland monitoring

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Authors: Guadalupe Pérez, Jorge Islas, Mirna Guevara, Raúl Suárez

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Jatropha curcas is a perennial oleaginous plant that is currently considered an energy crop with high potential as an environmentally sustainable biofuel. During the last decades, research in biofuels has grown in tropical and subtropical regions in Latin America. However, as far we know, there are no reports on the growth and yield patterns of Jatropha curcas under the specific agro climatic scenarios of the State of Morelos, Mexico. This study presents the results of 52 months monitoring of 10 toxic and non-toxic ecotypes of Jatropha curcas (E1M, E2M, E3M, E4M, E5M, E6O, E7O, E8O, E9C, E10C) in an experimental plantation with minimum watering and fertilization resources. The main objective is to identify the ecotypes with the highest potential as biodiesel raw material in the select region, by developing experimental information. Specifically, we monitored biophysical and growth parameters, including plant survival and seed production (at the end of month 52), to study the performance of each ecotype and to establish differences among the variables of morphological growth, net seed oil content, and toxicity. To analyze the morphological growth, a statistical approach to the biophysical parameters was used; the net seed oil content -80 to 192 kg/ha- was estimated with the first harvest; and the toxicity was evaluated by examining the phorbol ester concentration (µg/L) in the oil extracted from the seeds. The comparison and selection of ecotypes was performed through a methodology developed based on the normalization of results. We identified four outstanding ecotypes (E1M, E2M, E3M, and E4M) that can be used to establish Jatropha curcas as energy crops in the state of Morelos for feasible agro-industrial production of biodiesel and other products related to the use of biomass.

Keywords: biodiesel production, Jatropha curcas, seed oil content, toxic and non-toxic ecotypes

Procedia PDF Downloads 133

Authors: Shivam Dwivedi, Sumit Prakash Gupta, Durga Toshniwal

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It is a challenging task in today’s date to keep defence forces in the highest state of combat readiness with budgetary constraints. A huge amount of time and money is squandered in the unnecessary and expensive traditional maintenance activities. To overcome this limitation Defence Intelligent Mission Readiness and Maintenance Scheduling System has been proposed, which ameliorates the maintenance system by diagnosing the condition and predicting the maintenance requirements. Based on new data mining algorithms, this system intelligently optimises mission readiness for imminent operations and maintenance scheduling in repair echelons. With modified data mining algorithms such as Weighted Feature Ranking Genetic Algorithm and SVM-Random Forest Linear ensemble, it improves the reliability, availability and safety, alongside reducing maintenance cost and Equipment Out of Action (EOA) time. The results clearly conclude that the introduced algorithms have an edge over the conventional data mining algorithms. The system utilizing the intelligent condition-based maintenance approach improves the operational and maintenance decision strategy of the defence force.

Keywords: condition based maintenance, data mining, defence maintenance, ensemble, genetic algorithms, maintenance scheduling, mission capability

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Authors: Zhu Zhizheng, Huang Yong, Li Tong

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In the context of land and space development and resource environmental protection. Due to its special geographical location, mountain-plain transition zones are limited by many factors such as topography, mountain forest protection, etc., and their ecology is also more sensitive, with the characteristics of disaster susceptibility and resource gradient. Taking Dujiangyan City, Chengdu as an example, this paper establishes resilience evaluation indicators on the basis of ecological suitability evaluation through the analysis of current situation data and relevant policies: water conservation evaluation, soil and water conservation evaluation, biodiversity evaluation, soil erosion sensitivity evaluation, etc. Based on GIS spatial analysis, the ecological suitability and resilience evaluation results of Dujiangyan city were obtained by disjunction operation. The ecological resilience level of Dujiangyan city was divided into three categories: high, medium and low, with an area ratio of 50.81%, 16.4% and 32.79%, respectively. This paper can provide ideas for solving the contradiction between man and land in the mountain-plain transition zones, and also provide a certain basis for the construction of regional ecological protection and the delineation of three zones and three lines.

Keywords: urban and rural planning, ecological resilience, dujiangyan city, mountain-plain transition zones

Procedia PDF Downloads 111

Authors: Jorge R. Santos, Pedro Sebastiao

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In recent years there has been a great growth in the use of drones, being used in several areas such as security, agriculture, or research. The existence of some systems that allow the remote control of drones is a reality; however, these systems are quite simple and directed to specific functionality. This paper proposes the development of a web platform made in Vue.js and Node.js to control, manage, and monitor drones in real time. Using a microservice architecture, the proposed project will be able to integrate algorithms that allow the optimization of processes. Communication with remote devices is suggested via HTTP through 3G, 4G, and 5G networks and can be done in real time or by scheduling routes. This paper addresses the case of forest fires as one of the services that could be included in a system similar to the one presented. The results obtained with the elaboration of this project were a success. The communication between the web platform and drones allowed its remote control and monitoring. The incorporation of the fire detection algorithm in the platform proved possible a real time analysis of the images captured by the drone without human intervention. The proposed system has proved to be an asset to the use of drones in fire detection. The architecture of the application developed allows other algorithms to be implemented, obtaining a more complex application with clear expansion.

Keywords: drone control, microservices, node.js, unmanned aerial vehicles, vue.js

Procedia PDF Downloads 151

Authors: Joo-Heon Lee, Seo-Yeon Park, Chanyang Sur, Ho-Won Jang

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Satellite-based remote sensing technique has been widely used in the area of drought and environmental monitoring to overcome the weakness of in-situ based monitoring. There are many advantages of remote sensing for drought watch in terms of data accessibility, monitoring resolution and types of available hydro-meteorological data including environmental areas. This study was focused on the applicability of drought monitoring based on satellite imageries by applying to the historical drought events, which had a huge impact on meteorological, agricultural, and hydrological drought. Satellite-based drought indices, the Standardized Precipitation Index (SPI) using Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM); Vegetation Health Index (VHI) using MODIS based Land Surface Temperature (LST), and Normalized Difference Vegetation Index (NDVI); and Scaled Drought Condition Index (SDCI) were evaluated to assess its capability to analyze the complex topography of the Korean peninsula. While the VHI was accurate when capturing moderate drought conditions in agricultural drought-damaged areas, the SDCI was relatively well monitored in hydrological drought-damaged areas. In addition, this study found correlations among various drought indices and applicability using Receiver Operating Characteristic (ROC) method, which will expand our understanding of the relationships between hydro-meteorological variables and drought events at global scale. The results of this research are expected to assist decision makers in taking timely and appropriate action in order to save millions of lives in drought-damaged areas.

Keywords: drought monitoring, moderate resolution imaging spectroradiometer (MODIS), remote sensing, receiver operating characteristic (ROC)

Procedia PDF Downloads 329

Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

Procedia PDF Downloads 113

Authors: Mthokozisi Simelane

Abstract:

Background: Malaria remains a life-threatening disease in tropical regions despite the advances in the treatment of this disease, it still remains a significant burden as some parasites have become resistant to the currently available drugs. This has created a necessity for the development of alternative, more efficient antimalarial drugs. Warburgia salutaris is a traditional medicinal plant used in malaria treatment by Zulu traditional healers. Materials and methods: The W. salutaris stem-bark was extracted with dichloromethane and the compound was isolated through column chromatography. The compound was identified and characterized by spectroscopic analysis (1H NMR, 13C NMR, IR and MS) and the structure was also confirmed by x-ray crystallography. The anti-plasmodial activity (in vitro) was studied on NF54 Plasmodium falciparum strain (CQS). Cytotoxicity was measured using the MTT assay on HEK239 and HEPG2 cell lines. Docking of Mukaadial acetate was conducted in AutoDock Vina. Structural modifications were conducted in UCSF Chimera and molecular interactions examined in LigPlot. Results: The compound, Mukaadial Acetate showed appreciable inhibition (IC50 0.44±0.10 µg/ml) of the parasite growth and cytotoxicity activity of 0.124±0.109 and 0.199±0.083 (µg/ml) on HEK293 and HEPG2 cells respectively. Molecular docking revealed that Mukaadial Acetate binds to the purine, pyrophosphate and ribose binding sites of the PfHGXPRT with an optimum binding conformation and forms hydrogen bond, steric and hydrophobic interactions with the residues inhabiting the respective binding sites. Conclusion: It is apparent that W. salutaris contains components (including Mukaadial Acetate) that exhibit antimalarial activity. This study scientifically validates the use of this plant in folk medicine.

Keywords: plasmodium falciparum, molecular docking, antimalarial activity, PfHGXPRT, Warburgia salutaris, mukaadial acetate

Procedia PDF Downloads 199

Authors: Kitda Praraththajariya

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The main purpose of this research was to study how to communicate the identity of the Mueang district, SamutSongkram province for ecotourism. The qualitative data was collected through studying related materials, exploring the area, in-depth interviews with three groups of people: three directly responsible officers who were key informants of the district, twenty foreign tourists and five Thai tourist guides. A content analysis was used to analyze the qualitative data. The two main findings of the study were as follows: (1) The identity of Amphur (District) Mueang, SamutSongkram province. This establishment was near the Mouth of Maekong River for normal people and tourists, consisting of rest accommodations. There are restaurants where food and drinks are served, rich mangrove forests, Hoy Lod (Razor Clam) and mangrove trees. Don Hoy Lod, is characterized by muddy beaches, is a coastal wetland for Ramsar Site. It is at 1099th ranging where the greatest number of Hoy Lod (Razor Clam) can be seen from March to May each year. (2) The communication of the identity of AmphurMueang, SamutSongkram province which the researcher could find and design to present in English materials can be summed up in 4 items: 1) The history of AmphurMueang, SamutSongkram province 2) WatPhetSamutWorrawihan 3) The Learning source of Ecotourism: Don Hoy Lod and Mangrove forest 4) How to keep AmphurMueang, SamutSongkram province for ecotourism.

Keywords: foreigner tourists, signified, semiotics, ecotourism

Procedia PDF Downloads 305