Search results for: naturally regenerated acacia forest

Authors: Sunil Kumar

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For many years, small organic molecules derived naturally from microbes and plants have delivered a number of expedient therapeutic drug agents. The search for naturally occurring lead compounds has continued in recent years as well, with the constituents of marine flora and fauna along with those of telluric microorganisms and plants being investigated for their anti-bacterial and anti-cancer activities. It has been observed that such promising lead molecules incline to promptly generate substantial attention among scientists like synthetic organic chemists and biologists. Subsequently, the availability of a given precious natural product sample may be enriched, and it may be possible to determine a preliminary idea of structure-activity relationships to develop synthetic analogues. For instance, anti-tumor drug topotecan is a synthetic chemical compound similar in chemical structure to camptothecin which is found in extracts of Camptotheca acuminate. Similarly, researchers at AstraZeneca discovered anti-biotic pyrrolamide through a fragment-based lead generation approach from kibdelomycin, which is isolated from Staphylococcus aureuss.

Keywords: anticancer, antibiotic, lead molecule, natural product, synthetic analogues

Procedia PDF Downloads 152

Authors: Charles Akinola Imolehin

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According to the news on world population record, over 6.6 billion people on earth, and almost a quarter million added each day, the scale of human activity and environmental impact is unprecedented. Soaring human population growth over the past century has created a visible challenge to earth’s life support systems. Critical natural resources such as clean ground water, fertile topsoil, and biodiversity are diminishing at an exponential rate, orders of magnitude above that at which they can be regenerated. In addition, the world faces an onslaught of other environmental threats including degenerated global climate change, global warming, intensified acid rain, stratospheric ozone depletion and health threatening pollution. Overpopulation and the use of deleterious technologies combine to increase the scale of human activities to a level that underlies these entire problems. These intensifying trends cannot continue indefinitely, hopefully, through increased understanding and valuation of ecosystems and their services, earth’s basic life-support system will be protected for the future. To say the fact, human civilization is now the dominant cause of change in the global environment. Now that human relationship to the earth has change so utterly, there is need to see to that change and understand its implication. These are two aspects to the challenges which all should believe. The first is to realize that human activity has power to harm the earth and can indeed have global and even permanent effects. Second is to realize that the only way to understand human new role as a co-architect of nature is to see human activities as part of a complex system that does operate according to the same simple rules of cause and effect commonly used to. So, understanding the physical/biological dimension of earth system is an important precondition for making sensible policy to protect our environment. Because believing in Sustainable Development is a matter of reconciling respect for the environment, social equity, and economic profitability. Also, there is strong believe that environmental protection is naturally about reducing air and water pollution, but it also includes the improvement of the environmental performance of existing process. That is why is important to always have it at the heart of business policy that the environmental problem is not our effect on the environment so much as the relationship of production activities on the environment. There should be this positive thinking in all operation to always be environmentally friendly especially in projection and considering Sustainable ALL awareness in all sites of operation.

Keywords: earth's ocean, marine animals life under treat, flooding, ctritical natiural resouces polluted

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Authors: Abdallah Bouguettoucha, Derradji Chebli, Tariq Yahyaoui, Hichem Attout

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The effect of acid -basic treatment of lingocellulosic material (forest wastes wild carob) on Ethyl violet adsorption was investigated. It was found that surface chemistry plays an important role in Ethyl violet (EV) adsorption. HCl treatment produces more active acidic surface groups such as carboxylic and lactone, resulting in an increase in the adsorption of EV dye. The adsorption efficiency was higher for treated of lingocellulosic material with HCl than for treated with KOH. Maximum biosorption capacity was 170 and 130 mg/g, for treated of lingocellulosic material with HCl than for treated with KOH at pH 6 respectively. It was also found that the time to reach equilibrium takes less than 25 min for both treated materials. The adsorption of basic dye (i.e., ethyl violet or basic violet 4) was carried out by varying some process parameters, such as initial concentration, pH and temperature. The adsorption process can be well described by means of a pseudo-second-order reaction model showing that boundary layer resistance was not the rate-limiting step, as confirmed by intraparticle diffusion since the linear plot of Qt versus t^0.5 did not pass through the origin. In addition, experimental data were accurately expressed by the Sips equation if compared with the Langmuir and Freundlich isotherms. The values of ΔG° and ΔH° confirmed that the adsorption of EV on acid-basic treated forest wast wild carob was spontaneous and endothermic in nature. The positive values of ΔS° suggested an irregular increase of the randomness at the treated lingocellulosic material -solution interface during the adsorption process.

Keywords: adsorption, isotherm models, thermodynamic parameters, wild carob

Procedia PDF Downloads 277

Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman

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In this study, a multivariate analysis of potato spectroscopic data was presented to detect the presence of brown rot disease or not. Near-Infrared (NIR) spectroscopy (1,350-2,500 nm) combined with multivariate analysis was used as a rapid, non-destructive technique for the detection of brown rot disease in potatoes. Spectral measurements were performed in 565 samples, which were chosen randomly at the infection place in the potato slice. In this study, 254 infected and 311 uninfected (brown rot-free) samples were analyzed using different advanced statistical analysis techniques. The discrimination performance of different multivariate analysis techniques, including classification, pre-processing, and dimension reduction, were compared. Applying a random forest algorithm classifier with different pre-processing techniques to raw spectra had the best performance as the total classification accuracy of 98.7% was achieved in discriminating infected potatoes from control.

Keywords: Brown rot disease, NIR spectroscopy, potato, random forest

Procedia PDF Downloads 190

Authors: Angelica Salmeron Alcocer, Deifilia Ahuatzi Chacon, Felipe Rodriguez Casasola

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Polycyclic aromatic hydrocarbons (PAHs) are produced naturally (forest fires, volcanic eruptions) and human activity (burning fossil fuels). Concern for PAHs is due to their toxic, mutagenic and carcinogenic effects and so pose a potential risk to human health and ecology. Therefore these are considered the most toxic components of oil, they are highly hydrophobic, making them easily depositable on the floor, air and water. One method of removing PAHs of contaminated soil used surfactants such as Tween 80, which it has been reported as less toxic and also increases the solubility of the PAH compared to other surfactants, fluoranthene is a PAH with molecular formula C16H10, its name derives from the fluorescence which presents to UV light. In this paper, a study of the fluoranthene removal solubilized with Tween 80 in synthetic wastewater using a microbial community (isolated from soil of coffee plantations in the state of Veracruz, Mexico) and Fenton oxidation method was performed. The microbial community was able to use both tween 80 and fluoranthene as carbon sources for growth, when the biological treatment in batch culture was applied, 100% of fluoranthene was mineralized, this only occurred at an initial concentration of 100 ppm, but by increasing the initial concentration of fluoranthene the removal efficiencies decay and degradation time increases due to the accumulation of byproducts more toxic or less biodegradable, however when the Fenton oxidation was previously applied to the biological treatment, it was observed that removal of fluoranthene improved because it is consumed approximately 2.4 times faster.

Keywords: fluoranthene, polycyclic aromatic hydrocarbons, biological treatment, fenton oxidation

Procedia PDF Downloads 239

Authors: Keisuke Takahata, Hiroshi Suetsugu

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Forest height is an important parameter for forest biomass estimation, and precise elevation data is essential for accurate forest height estimation. There are several globally or nationally available digital elevation models (DEMs) like SRTM and ASTER. However, its accuracy is reported to be low particularly in mountainous areas where there are closed canopy or steep slope. Recently, space-borne LiDAR, such as the Global Ecosystem Dynamics Investigation (GEDI), have started to provide sparse but accurate ground elevation and canopy height estimates. Several studies have reported the high degree of accuracy in their elevation products on their exact footprints, while it is not clear how this sparse information can be used for wider area. In this study, we developed a digital terrain model correction algorithm by spatially interpolating the difference between existing DEMs and GEDI elevation products by using Gaussian Process (GP) regression model. The result shows that our GP-based methodology can reduce the mean bias of the elevation data from 3.7m to 0.3m when we use airborne LiDAR-derived elevation information as ground truth. Our algorithm is also capable of quantifying the elevation data uncertainty, which is critical requirement for biomass inventory. Upcoming satellite-LiDAR missions, like MOLI (Multi-footprint Observation Lidar and Imager), are expected to contribute to the more accurate digital terrain model generation.

Keywords: digital terrain model, satellite LiDAR, gaussian processes, uncertainty quantification

Procedia PDF Downloads 183

Authors: Majid Samiee Zenoozian

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This paper studies the susceptibility of local settlements in the gulf of Oman mangrove forest zone to flooding and progressesconsiderate of acuities and reactions to historical and present coastal flooding.it is indirect thaterosionsproduced in coastal zones by the change of mangrove undergrowthsubsequent from the enduring influence of persons since the late 19th century. Confronted with the increasing impact of climate change on climate ambitiousalarms such as flooding and biodiversity damage, handling the relationship between mangroves and their atmosphere has become authoritative for their defense. Coastal flood dangers are increasing quickly. We offer high resolution approximations of the financial value of mangroves forests for flood risk discount. We progress a probabilistic, process-based estimate of the properties of mangroves on avoidanceharms to people and property. More significantly, it also establishes how the incessantsqualor of this significant ecosystem has the potential to unfavorably influence the future cyclone persuadeddangers in the area.

Keywords: mangrove forest, coastal, flood, erosion

Procedia PDF Downloads 116

Authors: S. Y. Cicekli

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In this study, tree-dimensional model of tree was created by using terrestrial close range photogrammetry. For this close range photos were taken. Photomodeler Pro 5 software was used for camera calibration and create three-dimensional model of trees. In first test, three-dimensional model of a tree was created, in the second test three-dimensional model of three trees were created. This study aim is creating three-dimensional model of trees and indicate the use of close-range photogrammetry in forestry. At the end of the study, three-dimensional model of tree and three trees were created. This study showed that usability of close-range photogrammetry for monitoring tree and forests three-dimensional model.

Keywords: close- range photogrammetry, forest, tree, three-dimensional model

Procedia PDF Downloads 389

Authors: Basit Aftab, Zhichao Wang, Feng Zhongke

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Land Use and Land Cover Change (LULCC) is a critical environmental issue that has significant effects on biodiversity, ecosystem services, and climate change. This study examines the spatiotemporal dynamics of land use and land cover (LULC) across a three-decade period (1992–2022) in a district area. The goal is to support sustainable land management and urban planning by utilizing the combination of remote sensing, GIS data, and observations from Landsat satellites 5 and 8 to provide precise predictions of the trajectory of urban sprawl. In order to forecast the LULCC patterns, this study suggests a hybrid strategy that combines the Random Forest method with Multilayer Perceptron (MLP) and Markov Chain analysis. To predict the dynamics of LULC change for the year 2035, a hybrid technique based on multilayer Perceptron and Markov Chain Model Analysis (MLP-MCA) was employed. The area of developed land has increased significantly, while the amount of bare land, vegetation, and forest cover have all decreased. This is because the principal land types have changed due to population growth and economic expansion. The study also discovered that between 1998 and 2023, the built-up area increased by 468 km² as a result of the replacement of natural resources. It is estimated that 25.04% of the study area's urbanization will be increased by 2035. The performance of the model was confirmed with an overall accuracy of 90% and a kappa coefficient of around 0.89. It is important to use advanced predictive models to guide sustainable urban development strategies. It provides valuable insights for policymakers, land managers, and researchers to support sustainable land use planning, conservation efforts, and climate change mitigation strategies.

Keywords: land use land cover, Markov chain model, multi-layer perceptron, random forest, sustainable land, remote sensing.

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Authors: Md. Wasiul Islam, Md. Jamius Shams Sowrov

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The Sundarbans is the largest single tract of mangrove forest in the world. This is located in the southwest corner of Bangladesh. This is a unique ecosystem which is a great breeding and nursing ground for a great biodiversity. It supports the livelihood of about 3.5 million coastal dwellers and also protects the coastal belt and inland areas from various natural calamities. Historically, the management of the Sundarbans was controlled by the Bangladesh Forest Department following top-down approach without the involvement of local communities. Such fence and fining-based blue-print approach was not effective to protect the forest which caused Sundarbans to degrade severely in the recent past. Fifty percent of the total tree cover has been lost in the last 30 years. Therefore, local multi-stakeholder based bottom-up co-management approach was introduced at some of the parts of the Sundarbans in 2006 to improve the biodiversity status by enhancing the protection level of the forest. Various co-management organizations were introduced under co-management approach where the local community people could actively involve in various activities related to the management and welfare of the Sundarbans including the decision-making process to achieve the goal. From this backdrop, the objective of the study was to assess the performance of co-management organizations to facilitate sustainable management of the Sundarbans mangrove forests. The qualitative study followed face-to-face interview to collect data using two sets of semi-structured questionnaires. A total of 40 respondents participated in the research that was from eight villagers under two forest ranges. 32 representatives from the local communities as well as 8 official representatives involved in co-management approach were interviewed using snowball sampling technique. The study shows that the co-management approach improved governance system of the Sundarbans through active participation of the local community people and their interactions with the officials via the platform of co-management organizations. It facilitated accountability and transparency system to some extent through following some formal and informal rules and regulations. It also improved the power structure of the management process by fostering local empowerment process particularly the women. Moreover, people were able to learn from their interactions with and within the co-management organizations as well as interventions improved environmental awareness and promoted social learning. The respondents considered good governance as the most important factor for achieving the goal of sustainable management and biodiversity conservation of the Sundarbans. The success of co-management planning process also depends on the active and functional participation of different stakeholders including the local communities where co-management organizations were considered as the most functional platform. However, the governance system was also facing various challenges which resulted in barriers to the sustainable management of the Sundarbans mangrove forest. But still there were some members involved in illegal forest operations and created obstacles against sustainable management of the Sundarbans. Respondents recommended greater patronization from the government, financial and logistic incentives for alternative income generation opportunities with effective participatory monitoring and evaluation system to improve sustainable management of the Sundarbans.

Keywords: Bangladesh, co-management approach, co-management organizations, governance, Sundarbans, sustainable management

Procedia PDF Downloads 179

Authors: Natasha Gabriella, Josef-Peter Schöggl, Alfred Posch

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Being a mature industry, pulp and paper industry (PPI) possess strength points coming from its existing infrastructure, technology know-how, and abundant availability of biomass. However, the declining trend of the wood-based products sales sends a clear signal to the industry to transform its business model in order to increase its profitability. With the emerging global attention on bio-based economy and circular economy, coupled with the low price of fossil feedstock, the PPI starts to integrate biorefinery as a value-added business model to keep the industry’s competitiveness. Nonetheless, biorefinery as an innovation exposes the PPI with some barriers, of which the uncertainty of the promising product becomes one of the major hurdles. This study aims to assess factors that affect the diffusion and development of forest biorefinery in the PPI, including drivers, barriers, advantages, disadvantages, as well as the most promising bio-based products of forest biorefinery. The study examines the identified factors according to the layer of business environment, being the macro-environment, industry, and strategic group level. Besides, an overview of future state of the identified factors is elaborated as to map necessary improvements for implementing forest biorefinery. A two-phase Delphi method is used to collect the empirical data for the study, comprising of an online-based survey and interviews. Delphi method is an effective communication tools to elicit ideas from a group of experts to further reach a consensus of forecasting future trends. Collaborating a total of 50 experts in the panel, the study reveals that influential factors are found in every layers of business of the PPI. The politic dimension is apparent to have a significant influence for tackling the economy barrier while reinforcing the environmental and social benefits in the macro-environment. In the industry level, the biomass availability appears to be a strength point of the PPI while the knowledge gap on technology and market seem to be barriers. Consequently, cooperation with academia and the chemical industry has to be improved. Human resources issue is indicated as one important premise behind the preceding barrier, along with the indication of the PPI’s resistance towards biorefinery implementation as an innovation. Further, cellulose-based products are acknowledged for near-term product development whereas lignin-based products are emphasized to gain importance in the long-term future.

Keywords: forest biorefinery, pulp and paper, bio-based product, Delphi method

Procedia PDF Downloads 278

Authors: Sungzoon Cho, Hye Jin Lee, Sungwhan Jeon, Dongyoung Min, Sungwon Lyu

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Major public corporations worldwide use conference calls to report their quarterly earnings. These 'earnings' conference calls allow for questions from stock analysts. We investigated if it is possible to identify sentiment from the call script and use it to predict stock price movement. We analyzed call scripts from six companies, two each from Korea, China and Indonesia during six years 2011Q1 – 2017Q2. Random forest with Frequency-based sentiment scores using Loughran MacDonald Dictionary did better than control model with only financial indicators. When the stock prices went up 20 days from earnings release, our model predicted correctly 77% of time. When the model predicted 'up,' actual stock prices went up 65% of time. This preliminary result encourages us to investigate advanced sentiment scoring methodologies such as topic modeling, auto-encoder, and word2vec variants.

Keywords: earnings call script, random forest, sentiment analysis, stock price prediction

Procedia PDF Downloads 292

Authors: Harish Aryal, Thalia Balderas, Alondra Rodriguez

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Radioactivity present in nature possess a major challenge to public health and occupational concerns. Even at low doses, NORM can cause radiation-induced cancers, heritable diseases, genetic defects, etc. There have not been enough radiological studies and consequently, there is a lack of supportive data. In addition, there is no universal medical surveillance program for low-level doses and there is a need for NORM management guidelines for appropriate control. Naturally Occurring Radioactive Material (NORM) is present everywhere during oil/gas exploration. Currently, there is limited data available to quantify radioactivity. This research presents the study of radioactivity in different areas in the United States to be encouraged to be used for further study in Texas or similar areas within the oil and gas industry. Many materials that are found in the oil and gas industry are NORM (Naturally Occurring Radioactive Materials). The NORM is made of various types of materials, including Radium 226, Radium 228, and Radon 222. Efforts to characterize the geographic distribution of NORM have been limited by poor statistical representation in this area of study. In addition, the fate of NORM in the environment has not been fully defined, and few human health risk assessments have been conducted. To further comprehend how to measure radioactivity in oil and gas, it will be essential to understand the amount and type of radioactivity that is wasted on the water and soil of the industry.

Keywords: NORM, radium 226, radon 222, radionuclides, geological formations

Procedia PDF Downloads 89

Authors: Cheng-Yu Tsai, Wen-Te Liu, Shin-Mei Hsu, Yin-Tzu Lin, Chi Wu

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Background: Obstructive Sleep apnea syndrome (OSAS) is a common respiratory disorder during sleep. In addition, Body parameters were identified high predictive importance for OSAS severity. However, the effects of body parameters on OSAS severity remain unclear. Objective: In this study, the objective is to establish a prediction model for OSAS by using body parameters and investigate the effects of body parameters in OSAS. Methodologies: Severity was quantified as the polysomnography and the mean hourly number of greater than 3% dips in oxygen saturation during examination in a hospital in New Taipei City (Taiwan). Four levels of OSAS severity were classified by the apnea and hypopnea index (AHI) with American Academy of Sleep Medicine (AASM) guideline. Body parameters, including neck circumference, waist size, and body mass index (BMI) were obtained from questionnaire. Next, dividing the collecting subjects into two groups: training and testing groups. The training group was used to establish the random forest (RF) to predicting, and test group was used to evaluated the accuracy of classification. Results: There were 3330 subjects recruited in this study, whom had been done polysomnography for evaluating severity for OSAS. A RF of 1000 trees achieved correctly classified 79.94 % of test cases. When further evaluated on the test cohort, RF showed the waist and BMI as the high import factors in OSAS. Conclusion It is possible to provide patient with prescreening by body parameters which can pre-evaluate the health risks.

Keywords: apnea and hypopnea index, Body parameters, obstructive sleep apnea syndrome, Random Forest

Procedia PDF Downloads 153

Authors: Riccardo Zanni, Maria Galvez-Llompart, Ramon Garcia-Domenech, Jorge Galvez

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Biopesticides, such as naturally occurring chemicals, pheromones, fungi, bacteria and insect predators are often a winning choice in crop protection because of their environmental friendly profile. They are considered to have lower toxicity than traditional pesticides. After almost a century of pesticides use, resistances to traditional insecticides are wide spread, while those to bioinsecticides have raised less attention, and resistance management is frequently neglected. This seems to be a crucial mistake since resistances have already occurred for many marketed biopesticides. With an eye to the future, we present here a selection of new natural occurring chemicals as potential bioinsecticides. The molecules were selected using a consolidated mathematical paradigm called molecular topology. Several QSAR equations were depicted and subsequently applied for the virtual screening of hundred thousands molecules of natural origin, which resulted in the selection of new potential bioinsecticides. The most innovative aspect of this work does not only reside in the importance of the identification of new molecules overcoming biopesticides’ resistances, but on the possibility to promote shared knowledge in the field of green chemistry through this unique in silico discipline named molecular topology.

Keywords: green chemistry, QSAR, molecular topology, biopesticide

Procedia PDF Downloads 315

Authors: Sarah Ryu

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Agricultural methods and ecological approaches employed by the pre-colonial Mayans may provide valuable insights into forest management and viable alternatives for resource sustainability in the face of major deforestation across Central and South America.Using a combination of observation data collected from the modern indigenous inhabitants near Mixco in Guatemala and historical data, this study was able to create a holistic picture of how the Maya maintained their ecosystems. Surveys and observations were conducted in the field, over a period of twelve weeks across two years. Geographic and archaeological data for this area was provided by Guatemalan organizations such as the Universidad de San Carlos de Guatemala. Observations of current indigenous populations around Mixco showed that they adhered to traditional Mayan methods of agriculture, such as terrace construction and arboriculture. Rather than planting one cash crop as was done by the Spanish, indigenous peoples practice agroforestry, cultivating forests that would provide trees for construction material, wild plant foods, habitat for game, and medicinal herbs. The emphasis on biodiversity prevented deforestation and created a sustainable balance between human consumption and forest regrowth. Historical data provided by MayaSim showed that the Mayans successfully maintained their ecosystems from about 800BCE to 700CE. When the Mayans practiced natural resource conservation and cultivated a harmonious relationship with the forest around them, they were able to thrive and prosper alongside nature. Having lasted over a thousand years, the Mayan empire provides a valuable lesson in sustainability and human attitudes towards the environment.

Keywords: biodiversity, forestry, mayan, sustainability

Procedia PDF Downloads 177

Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Abdelaziz Wided, Khiat Nawel, Khiat Inssaf

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The present study was initiated to: Determine burned forest-inhabiting fungi in Zouagha, Terri Beinène, Mila and study the antagonistic activity of Trichoderma sp against Fusarium sp, Penicillium sp, Rhizoctonia sp, Alternaria sp. 18 fungal strains were isolated from Soil samples taken from the forest Zouagha (Burned) in the region Mila representing 6 genera: Trichoderma sp et Fusarium sp, Penicillium sp, Rhizoctonia sp, Alternaria sp, Rhizopus sp. The tests of dual culture method on culture medium (PDA) against Trichoderma sp et Fusarium sp, Penicillium sp, Rhizoctonia sp, Alternaria sp revealed that: Trichoderma sp could reduce l mycelium grouth of Fusarium sp23.13%, Penicillium sp33.13%, Rhizoctoniasp33.75 %and Alternaria sp 38.31% in comparaison with the witness after 6 days at room temperature. The strains of Fusarium sp ,Penicillium sp, Rhizoctonia sp et Alternaria sp showed differences sensibility to the antagoniste.

Keywords: isolation, identification, molds, burned soil of zouagha, antagonism, trichoderma sp

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Authors: Mohd Firrdhaus Mohd Sahabuddin, Cristina Gonzalez-Longo

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Large migration from rural areas to urban areas like Kuala Lumpur has led to some implications for economic, social and cultural development. This high population has placed enormous demand on the existing housing stocks, especially for low-income groups. However, some issues arise, one of which is overheated indoor air temperature. This problem contributes to the high-energy usage that forces huge sums of money to be spent on cooling the house by using mechanical equipment. Therefore, this study focuses on thermal comfort in social housing, and incorporates traditional values into its design to achieve a certain measurement of natural ventilation in a house. From the study, the carbon emission and energy consumption for an air-conditioned house is 67%, 66% higher than a naturally ventilated house. Therefore, this research has come up with a new typology design, which has a large exposed wall area and full-length openings on the opposite walls to increase cross ventilation. At the end of this research, the measurement of thermal comfort for a naturally ventilated building called ‘AirHouse’ has been identified.

Keywords: tropical architecture, natural ventilation, passive design, AirHouse, social housing design

Procedia PDF Downloads 676

Authors: Abraha Hatsey, Nesibu Yahya, Abeje Eshete

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Ethiopian Orthodox Tewahido Church has a long tradition of conserving the Church vegetation and is an area treated as a refugee camp for many endangered indigenous tree species in Northern Ethiopia. Though around 36,000 churches exist in Ethiopia, only a few churches have been studied so far. Thus, this study assessed the land use land cover change of 3km buffer (1986-2018) and the woody species diversity and regeneration status of Tsimur St. Gebriel monastery in Tigray region, Northern Ethiopia. For vegetation study, systematic sampling was used with 100m spacing between plots and between transects. Plot size was 20m*20m for the main plot and 2 subplots (5m*5m each) for the regeneration study. Tree height, diameter at breast height(DBH) and crown area were measured in the main plot for all trees with DBH ≥ 5cm. In the subplots, all seedlings and saplings were counted with DBH < 5cm. The data was analyzed on excel and Pass biodiversity software for diversity and evenness analysis. The major land cover classes identified include bare land, farmland, forest, shrubland and wetland. The extents of forest and shrubland were declined considerably due to bare land and agricultural land expansions within the 3km buffer, indicating an increasing pressure on the church forest. Regarding the vegetation status, A total of 19 species belonging to 13 families were recorded in the monastery. The diversity (H’) and evenness recorded were 2.4 and 0.5, respectively. The tree density (DBH ≥ 5cm) was 336/ha and a crown cover of 65%. Olea europaea was the dominant (6.4m2/ha out of 10.5m2 total basal area) and a frequent species (100%) with good regeneration in the monastery. The rest of the species are less frequent and are mostly confined to water sources with good site conditions. Juniperus procera (overharvested) and the other indigenous species were with few trees left and with no/very poor regeneration status. The species having poor density, frequency and regeneration (Junperus procera, Nuxia congesta Fersen and Jasminium abyssinica) need prior conservation and enrichment planting. The indigenous species could also serve as a potential seed source for the reproduction and restoration of nearby degraded landscapes. The buffer study also demonstrated expansion of agriculture and bare land, which could be a threat to the forest of the isolated monastery. Hence, restoring the buffer zone is the only guarantee for the healthy existence of the church forest.

Keywords: church forests, regeneration, land use change, vegetation status

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Authors: Jozef Mindas, Jaroslav Skvarenina, Jana Skvareninova

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Study of the effects of climate change on Norway Spruce (Picea abies) forests has mainly focused on the diversity of tree species diversity of tree species as a result of the ability of species to tolerate temperature and moisture changes as well as some effects of disturbance regime changes. The tree species’ diversity changes in spruce forests due to climate change have been analyzed via gap model. Forest gap model is a dynamic model for calculation basic characteristics of individual forest trees. Input ecological data for model calculations have been taken from the permanent research plots located in primeval forests in mountainous regions in Slovakia. The results of regional scenarios of the climatic change for the territory of Slovakia have been used, from which the values are according to the CGCM3.1 (global) model, KNMI and MPI (regional) models. Model results for conditions of the climate change scenarios suggest a shift of the upper forest limit to the region of the present subalpine zone, in supramontane zone. N. spruce representation will decrease at the expense of beech and precious broadleaved species (Acer sp., Sorbus sp., Fraxinus sp.). The most significant tree species diversity changes have been identified for the upper tree line and current belt of dwarf pine (Pinus mugo) occurrence. The results have been also discussed in relation to most important disturbances (wind storms, snow and ice storms) and phenological changes which consequences are little known. Special discussion is focused on biomass production changes in relation to carbon storage diversity in different carbon pools.

Keywords: biodiversity, climate change, Norway spruce forests, gap model

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Authors: Eric Mensah

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The effects of rapid urbanisation of tropical sub-Saharan developing cities on local and global climate are of great concern due to the negative impacts of Urban Heat Island (UHI) effects. The importance of urban parks, vegetative cover and forest reserves in these tropical cities have been undervalued with a rapid degradation and loss of these vegetative covers to urban developments which continue to cause an increase in daily mean temperatures and changes to local climatic conditions. Using Landsat data of the same months and period intervals, the spatial variations of land cover changes, temperature, and vegetation were examined to determine how vegetation improves local temperature and the effects of urbanisation on daily mean temperatures over the past 12 years. The remote sensing techniques of maximum likelihood supervised classification, land surface temperature retrieval technique, and normalised differential vegetation index techniques were used to analyse and create the land use land cover (LULC), land surface temperature (LST), and vegetation and non-vegetation cover maps respectively. Results from the study showed an increase in daily mean temperature by 0.80 °C as a result of rapid increase in urban area by 46.13 sq. km and loss of vegetative cover by 46.24 sq. km between 2005 and 2017. The LST map also shows the existence of UHI within the urban areas of Accra, the potential mitigating effects offered by the existence of forest and vegetative cover as demonstrated by the existence of cool islands around the Achimota ecological forest and University of Ghana botanical gardens areas.

Keywords: land surface temperature, climate, remote sensing, urbanisation

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Authors: Valmir Baloshi, Fran Gjoka, Nehat Çollaku, Elvin Toromani

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As a sediment production mechanism, soil erosion is the main environmental threat to the Bovilla watershed, including the decline of water quality of the Bovilla reservoir that provides drinking water to Tirana city (the capital of Albania). Therefore, an experiment with 25 erosion plots for soil erosion monitoring has been set up since June 2017. The aim was to determine the soil loss on plot and watershed scale in Bovilla watershed (Tirana region) for implementation of soil and water protection measures or payments for ecosystem services (PES) programs. The results of erosion monitoring for the period June 2017 - May 2018 showed that the highest values of surface runoff were noted in bare land of 38829.91 liters on slope of 74% and the lowest values in forest land of 12840.6 liters on slope of 64% while the highest values of soil loss were found in bare land of 595.15 t/ha on slope of 62% and lowest values in forest land of 18.99 t/ha on slope of 64%. These values are much higher than the average rate of soil loss in the European Union (2.46 ton/ha/year). In the same sloping class, the soil loss was reduced from orchard or bare land to the forest land, and in the same category of land use, the soil loss increased with increasing land slope. It is necessary to conduct chemical analyses of sediments to determine the amount of chemical elements leached out of the soil and end up in the reservoir of Bovilla. It is concluded that PES programs should be implemented for rehabilitation of sub-watersheds Ranxe, Vilez and Zall-Bastar of the Bovilla watershed with valuable conservation practices.

Keywords: ANOVA, Bovilla, land cover, slope, soil loss, watershed management

Procedia PDF Downloads 162

Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

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In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

Procedia PDF Downloads 53

Authors: Bencherif Kada

Abstract:

In the forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape, and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification, that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction, and area of an object, etc.), and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify of the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak, and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants, and bare soils. Texture attributes seem to provide no useful information, while spatial attributes of shape and compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.

Keywords: forest, oaks, remote sensing, diversity, shrublands

Procedia PDF Downloads 124

Authors: Lea Lenhardt, Ivana Zeković, Tatjana Dramićanin, Miroslav D. Dramićanin

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Fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC) and artificial neural networks (ANN) were used for characterization and classification of honey. Excitation emission spectra were obtained for 95 honey samples of different botanical origin (acacia, sunflower, linden, meadow, and fake honey) by recording emission from 270 to 640 nm with excitation in the range of 240-500 nm. Fluorescence spectra were described with a six-component PARAFAC model, and PARAFAC scores were further processed with two types of ANN’s (feed-forward network and self-organizing maps) to obtain algorithms for classification of honey on the basis of their botanical origin. Both ANN’s detected fake honey samples with 100% sensitivity and specificity.

Keywords: honey, fluorescence, PARAFAC, artificial neural networks

Procedia PDF Downloads 954

Authors: Rafael Castilho Carvalho, Edjair de Souza Mota

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As the largest contributor to the biogeochemical functioning of the Earth system, the Amazon Rainforest has the greatest biodiversity on the planet, harboring about 15% of all the world's flora. Recognition and preservation are the focus of research that seeks to mitigate drastic changes, especially anthropic ones, which irreversibly affect this biome. Functional and low-cost monitoring alternatives to reduce these impacts are a priority, such as those using technologies such as Low Power Wide Area Networks (LPWAN). Promising, reliable, secure and with low energy consumption, LPWAN can connect thousands of IoT devices, and in particular, LoRa is considered one of the most successful solutions to facilitate forest monitoring applications. Despite this, the forest environment, in particular the Amazon Rainforest, is a challenge for these technologies, requiring work to identify and validate the use of technology in a real environment. To investigate the feasibility of deploying LPWAN in remote water quality monitoring of rivers in the Amazon Region, a LoRa-based test bed consisting of a Lora transmitter and a LoRa receiver was set up, both parts were implemented with Arduino and the LoRa chip SX1276. The experiment was carried out at the Federal University of Amazonas, which contains one of the largest urban forests in Brazil. There are several springs inside the forest, and the main goal is to collect water quality parameters and transmit the data through the forest in real time to the gateway at the uni. In all, there are nine water quality parameters of interest. Even with a high collection frequency, the amount of information that must be sent to the gateway is small. However, for this application, the battery of the transmitter device is a concern since, in the real application, the device must run without maintenance for long periods of time. With these constraints in mind, parameters such as Spreading Factor (SF) and Coding Rate (CR), different antenna heights, and distances were tuned to better the connectivity quality, measured with RSSI and loss rate. A handheld spectrum analyzer RF Explorer was used to get the RSSI values. Distances exceeding 200 m have soon proven difficult to establish communication due to the dense foliage and high humidity. The optimal combinations of SF-CR values were 8-5 and 9-5, showing the lowest packet loss rates, 5% and 17%, respectively, with a signal strength of approximately -120 dBm, these being the best settings for this study so far. The rains and climate changes imposed limitations on the equipment, and more tests are already being conducted. Subsequently, the range of the LoRa configuration must be extended using a mesh topology, especially because at least three different collection points in the same water body are required.

Keywords: IoT, LPWAN, LoRa, coverage, loss rate, forest

Procedia PDF Downloads 89

Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

Abstract:

The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

Procedia PDF Downloads 51

Authors: Aklilu Getahun Sulito

Abstract:

Land Use and Land Cover change dynamics is a result of complex interactions betweenseveral bio- physical and socio-economic conditions. The impacts of the landcoverchange on stream flow and sediment yield were analyzed statistically usingthehydrological model, SWAT. Genale Dawa Dam III watershed is highly af ectedbydeforestation, over grazing, and agricultural land expansion. This study was aimedusingSWAT model for the assessment of impacts of land use land cover change on sediment yield, evaluating stream flow on wet &dry seasons and spatial distribution sediment yieldfrom sub-basins of the Genale Dawa Dam III watershed. Land use land cover maps(LULC) of 2000, 2008 and 2016 were used with same corresponding climate data. During the study period most parts of the forest, dense forest evergreen and grass landchanged to cultivated land. The cultivated land increased by 26.2%but forest land, forest evergreen lands and grass lands decreased by 21.33%, 11.59 % and 7.28 %respectively, following that the mean annual sediment yield of watershed increased by 7.37ton/haover16 years period (2000 – 2016). The analysis of stream flow for wet and dry seasonsshowed that the steam flow increased by 25.5% during wet season, but decreasedby29.6% in the dry season. The result an average annual spatial distribution of sediment yield increased by 7.73ton/ha yr -1 from (2000_2016). The calibration results for bothstream flow and sediment yield showed good agreement between observed and simulateddata with the coef icient of determination of 0.87 and 0.84, Nash-Sutclif e ef iciencyequality to 0.83 and 0.78 and percentage bias of -7.39% and -10.90%respectively. Andthe result for validation for both stream flow and sediment showed good result withCoef icient of determination equality to 0.83 and 0.80, Nash-Sutclif e ef iciency of 0.78and 0.75 and percentage bias of 7.09% and 3.95%. The result obtained fromthe model based on the above method was the mean annual sediment load at Genale DawaDamIIIwatershed increase from 2000 to 2016 for the reason that of the land uses change. Sotouse the Genale Dawa Dam III the land use management practices are neededinthefuture to prevent further increase of sediment yield of the watershed.

Keywords: Genale Dawa Dam III watershed, land use land cover change, SWAT, spatial distribution, sediment yield, stream flow

Procedia PDF Downloads 55

Authors: Bisi-Johnson, Mary A., Hamzart A. Oyelade, Kehinde A. Adediran, Saheed A. Akinola

Abstract:

Geophagic and cosmetic clays are among potential nano-material which occur naturally and are of various forms. The use of these nano-clays is a common practice in both rural and urban areas mostly due to tradition and medicinal reasons. These naturally occurring materials can be valuable sources of nano-material by serving as nano-composites. The need to ascertain the safety of these materials is the motivation for this research. Physical Characterization based on the hue value and microbiological qualities of the nano-clays were carried out. The Microbial analysis of the clay samples showed considerable contamination with both bacteria and fungi with fungal contaminants taking the lead. This observation may not be unlikely due to the ability of fungi species to survive harsher growth conditions than bacteria. 'Atike pupa' showed no bacterial growth. The clay with the largest bacterial count was Calabash chalk (Igbanke), while that with the highest fungal count was 'Eko grey'. The most commonly isolated bacteria in this study were Clostridium spp. and Corynebacterium spp. while fungi included Aspergillus spp. These results are an indication of the need to subject these clay materials to treatments such as heating before consumption or topical usage thereby ascertaining their safety.

Keywords: nano-material, clay, microorganism, quality

Procedia PDF Downloads 396