Search results for: gallery forest

Authors: Olusegun D. Badewa, E. K. Tsado, A. S. Gana, K. D. Tolorunse, R. U. Okechukwu, P. Iluebbey, S. Ibrahim

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Farmers are faced with varying production challenges ranging from unstable weather due to climate change, low yield, malnutrition, cattle invasion, and bush fires that have always affected their livelihood. Research effort must therefore be centered on improving farmers’ livelihood, nutrition, and health by providing early bulking biofortified cassava varieties that could be harvested earlier with reasonable root yield and thereby preventing long stay of the crop on their farmland. This study evaluated cassava genotypes at different harvesting months of 3, 6, 9, and 12 months after planting in order to evaluate their bulking rate at different agroecology of Mokwa and Ubiaja. Data were collected on fresh storage root yield, Harvest index, and Dry matter content. It was shown from the study that traits FSRY, HI, and DM were significant for genotype and months after planting and variable among the genotype while location had no effect on the yield traits. Early bulking genotypes were not high yielding and showed discontinuity at some point across the months. The retrogression in yield performance across months had no effect on the highest yielding. Also, for all the genotypes and across evaluated months, FSRY reduces at 9 MAP due to a reduction in dry matter content during the same month, and the best performing genotype was the genotype IBA90581, followed by IBA120036, IBA130896, and IBA980581 while the least performing was genotype IBA130818.

Keywords: early bulking, dry mater, harvest index, high yielding, root yield

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Authors: Yusuf Jundi Sado

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Changes in land use are mostly credited to human actions that result in negative impacts on biodiversity and ecosystem functions. This study aims to analyze the dynamics of land use and land cover changes for sustainable natural resources planning and management. Chilalo-Galama Mountain Range, Ethiopia. This study used Thematic Mapper 05 (TM) for 1986, 2001 and Landsat 8 (OLI) data 2017. Additionally, data from the Central Statistics Agency on human population growth were analyzed. Semi-Automatic classification plugin (SCP) in QGIS 3.2.3 software was used for image classification. Global positioning system, field observations and focus group discussions were used for ground verification. Land Use Land Cover (LU/LC) change analysis was using maximum likelihood supervised classification and changes were calculated for the 1986–2001 and the 2001–2017 and 1986-2017 periods. The results show that agricultural land increased from 27.85% (1986) to 44.43% and 51.32% in 2001 and 2017, respectively with the overall accuracies of 92% (1986), 90.36% (2001), and 88% (2017). On the other hand, forests decreased from 8.51% (1986) to 7.64 (2001) and 4.46% (2017), and grassland decreased from 37.47% (1986) to 15.22%, and 15.01% in 2001 and 2017, respectively. It indicates for the years 1986–2017 the largest area cover gain of agricultural land was obtained from grassland. The matrix also shows that shrubland gained land from agricultural land, afro-alpine, and forest land. Population dynamics is found to be one of the major driving forces for the LU/LU changes in the study area.

Keywords: Landsat, LU/LC change, Semi-Automatic classification plugin, population dynamics, Ethiopia

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Authors: Ananya Mitra Pramanik, Anjali Agrawal

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The objective of this paper is to trace the origin and evolution of clothing in the Indian Subcontinent. The paper seeks to understand the need for mankind to shed his natural state and adopt clothing as an inseparable accessory for his body. It explores the various theories of the origin of clothing. The known journey of clothing of this region started from the Indus Valley Civilisation which dates back to 2500 BC. Due to the weather conditions of the region, few actual samples have survived, and most of the knowledge of textiles is derived from the sculptures and other remains from this era. The understanding of textiles of the period after the Indus Valley Civilisation (2500-1500 BC) till the Mauryan and the Sunga Period (321-72 BC) comes from literary sources, e.g., Vedas, Smritis, the eminent Indian epics of the Ramayana and the Mahabharata, forest books, etc. Textile production was one of the most important economic activities of this region. It was next only to agriculture. While attempting to trace the history of clothing the paper draws the evolution of Indian traditional fashion through the change of rulers of this region and the development of the modern Indian traditional dress, i.e., sari, salwar kamiz, dhoti, etc. The major aims of the study are to define the different time periods chronologically and to inspect the major changes in textile fashion, manufacturing, and materials that took place. This study is based on secondary research. It is founded on data taken primarily from books and journals. Not much of visuals are added in the paper as actual fabric references are near nonexistent. It gives a brief history of the ancient textiles of India from the time frame of 2500 BC-8th C AD.

Keywords: evolution, history, origin, textiles

Procedia PDF Downloads 151

Authors: Erich Gomes Schaitza, Antônio Francisco Savi, Glaucia Aparecida Prates

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The penetration of renewable energy into the electricity supply in Brazil is high, one of the highest in the World. Centralized hydroelectric generation is the main source of energy, followed by biomass and wind. Surprisingly, mini and micro-generation are negligible, with less than 2,000 connections to the national grid. In 2015, a new regulatory framework was put in place to change this situation. In the agricultural sector, the framework was complemented by the offer of low interest rate loans to in-farm renewable generation. Brazil proposed to more than double its area of planted forests as part of its INDC- Intended Nationally Determined Contributions to the UNFCCC-U.N. Framework Convention on Climate Change (UNFCCC). This is an ambitious target which will be achieved only if forests are attractive to farmers. Therefore, this paper analyses whether planting forests for in-farm energy generation with a with a woodchip gasifier is economically viable for microgeneration under the new framework and at if they could be an economic driver for forest plantation. At first, a static case was analyzed with data from Eucalyptus plantations in five farms. Then, a broader analysis developed with the use of Monte Carlo technique. Planting short rotation forests to generate energy could be a viable alternative and the low interest loans contribute to that. There are some barriers to such systems such as the inexistence of a mature market for small scale equipment and of a reference network of good practices and examples.

Keywords: biomass, distribuited generation, small-scale, Monte Carlo

Procedia PDF Downloads 259

Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

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Authors: Nor Anisa

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This paper aims to describe the use of conservation and rehabilitation of Mangrove forests as an alternative area in protecting the natural environment and ecosystems and ecology, community education and innovation of sustainable industrial development such as oil companies, gas and coal. The existence of globalization encourages energy needs such as gas, diesel and coal as an unaffected resource which is a basic need for human life while environmental degradation and natural phenomena continue to occur in Indonesia, especially global warming, sea water pollution, extinction of animal steps. The phenomenon or damage to nature in Indonesia is caused by a population explosion in Indonesia that causes unemployment, the land where the residence will disappear so that this will encourage the exploitation of nature and the environment. Therefore, Pertamina as a state-owned oil and gas company carries out its social responsibility efforts, namely to carry out conservation and rehabilitation and management of Mangrove fruit seeds which will provide an educational effect on the benefits of Mangrove seed maintenance. The method used in this study is a qualitative method and secondary data retrieval techniques where data is taken based on Pertamina activity journals and websites that can be accounted for. So the conclusion of this paper is: the benefits and function of conservation of mangrove forests in Indonesia physically, chemically, biologically and socially and economically and can provide innovation to the CSR (Corporate Social Responsibility) of the company in continuing social responsibility in the scope of environmental conservation and social education.

Keywords: mangrove, environmental damage, conservation and rehabilitation, innovation of corporate social responsibility

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Authors: Suraj Sharma

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Green infrastructure (GI) offers a contemporary approach for reducing the risk of flooding, improve water quality, and harvesting stormwater for sustainable use. GI promotes landscape planning to enhance sustainable development and urban resilience. However, the existing literature is lacking in ensuring the comprehensive assessment of GI performance in terms of ecosystem function and services for social, ecological, and economical system resilience. We propose a robust indicator set and fuzzy comprehensive evaluation (FCE) for quantitative and qualitative analysis for sustainable water management to assess the capacity of urban resilience. Green infrastructure in urban resilience water management system (GIUR-WMS) supports decision-making for GI planning through scenario comparisons with urban resilience capacity index. To demonstrate the GIUR-WMS, we develop five scenarios for five sectors of Chandigarh (12, 26, 14, 17, and 34) to test common type of GI (rain barrel, rain gardens, detention basins, porous pavements, and open spaces). The result shows the open spaces achieve the highest green infrastructure urban resilience index of 4.22/5. To implement the open space scenario in urban sites, suitable vacant can be converted to green spaces (example: forest, low impact recreation areas, and detention basins) GIUR-WMS is easy to replicate, customize and apply to cities of different sizes to assess environmental, social and ecological dimensions.

Keywords: green infrastructure, assessment, urban resilience, water management system, fuzzy comprehensive evaluation

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Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

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Authors: Herawanti Kumalasari, Raldi Hendro Koestoer, Hayati Sari Hasibuan

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Geographically, Indonesia is located in the arc of volcanoes that cause disaster prone one of them is landslide disaster. One of the causes of the landslide is the conversion of land from forest to agricultural land in upland areas and river border that has a steep slope. The study area is located in the highlands with fertile soil conditions, so most of the land is used as agricultural land and plantations. Land use transfer also occurs around the geothermal field in Pangalengan District, West Java Province which will threaten the sustainability of geothermal energy utilization and the safety of the community. The purpose of this research is to arrange the concept of spatial pattern arrangement in the geothermal area based on disaster mitigation. This research method using superimpose analysis. Superimpose analysis to know the basic physical condition of the planned area through the overlay of disaster risk map with the map of the plan of spatial plan pattern of Bandung Regency Spatial Plan. The results of the analysis will then be analyzed spatially. The results have shown that most of the study areas were at moderate risk level. Planning of spatial pattern of existing study area has not fully considering the spread of disaster risk that there are settlement area and the agricultural area which is in high landslide risk area. The concept of the arrangement of the spatial pattern of the study area will use zoning system which is divided into three zones namely core zone, buffer zone and development zone.

Keywords: spatial planning, geothermal, disaster risk, zoning

Procedia PDF Downloads 246

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

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Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi

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Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.

Keywords: time-series clustering, feature extraction, hoax prediction, geospatial events

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Yoshinori Wakatake

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Many defects after the release of software packages are caused due to omissions of sufficient test items in test specifications. Poor test specifications are detected by manual review, which imposes a high human load. The prevention of omissions depends on the end-user awareness of test specification writers. If test specifications were written while envisioning the behavior of end-users, the number of omissions in test items would be greatly reduced. The paper pays attention to the point that writers who can achieve it differ from those who cannot in not only the description richness but also their gaze information. It proposes a method to estimate the degree of user-awareness of writers through the analysis of their gaze information when writing test specifications. We conduct an experiment to obtain the gaze information of a writer of the test specifications. Test specifications are automatically classified using gaze information. In this method, a Random Forest model is constructed for the classification. The classification is highly accurate. By looking at the explanatory variables which turn out to be important variables, we know behavioral features to distinguish test specifications of high quality from others. It is confirmed they are pupil diameter size and the number and the duration of blinks. The paper also investigates test specifications automatically classified with gaze information to discuss features in their writing ways in each quality level. The proposed method enables us to automatically classify test specifications. It also prevents test item omissions, because it reveals writing features that test specifications of high quality should satisfy.

Keywords: blink, eye tracking, gaze information, pupil diameter, quality improvement, specification document, user-awareness

Procedia PDF Downloads 39

Authors: Penrug Pengsombut, Worawut Hamarn, Teerawuth Suwannasri, Kittiphong Songrukkiat, Kanatip Ratanachoo

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PTT Public Company Limited or simply PTT has played an important role in strengthening national energy security of the Kingdom of Thailand by transporting natural gas to customers in power, industrial and commercial sectors since 1981. PTT has been constructing and operating natural gas pipeline system of over 4,500-km network length both onshore and offshore laid through different area classifications i.e., marine, forest, agriculture, rural, urban, and city areas. During project development phase, an Environmental Impact Assessment (EIA) is conducted and submitted to the Office of Natural Resources and Environmental Policy and Planning (ONEP) for approval before project construction commencement. Knowledge and experiences gained and revealed from EIA in the past projects definitely are developed to further advance EIA study process for newly 5th Transmission Natural Gas Pipeline Project (5TP) with approximately 415 kilometers length. The preferred pipeline route is selected and justified by SMARTi map, an advance digital one-map platform with consists of multiple layers geographic and environmental information. Sensitive area impact focus (SAIF) is a practicable impact assessment methodology which appropriate for a particular long distance infrastructure project such as 5TP. An environmental modeling simulation is adopted into SAIF methodology for impact quantified in all sensitive areas whereas other area along pipeline right-of-ways is typically assessed as an impact representative. Resulting time and cost deduction is beneficial to project for early start.

Keywords: environmental impact assessment, EIA, natural gas pipeline, sensitive area impact focus, SAIF

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Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

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Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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Authors: Fariza Yunus, Jasmee Jaafar, Zamalia Mahmud, Nurul Nisa’ Khairul Azmi, Nursalleh K. Chang, Nursalleh K. Chang

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Variation of air temperature from one place to another is cause by air temperature controls. In general, the most important control of air temperature is elevation. Another significant independent variable in estimating air temperature is the location of meteorological stations. Distances to coastline and land use type are also contributed to significant variations in the air temperature. On the other hand, in homogeneous terrain direct interpolation of discrete points of air temperature work well to estimate air temperature values in un-sampled area. In this process the estimation is solely based on discrete points of air temperature. However, this study presents that air temperature controls also play significant roles in estimating air temperature over homogenous terrain of Peninsular Malaysia. An Inverse Distance Weighting (IDW) interpolation technique was adopted to generate continuous data of air temperature. This study compared two different datasets, observed mean monthly data of T, and estimation error of T–T’, where T’ estimated value from a multiple regression model. The multiple regression model considered eight independent variables of elevation, latitude, longitude, coastline, and four land use types of water bodies, forest, agriculture and build up areas, to represent the role of air temperature controls. Cross validation analysis was conducted to review accuracy of the estimation values. Final results show, estimation values of T–T’ produced lower errors for mean monthly mean air temperature over homogeneous terrain in Peninsular Malaysia.

Keywords: air temperature control, interpolation analysis, peninsular Malaysia, regression model, air temperature

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Authors: Neeraj Malhotra, Ramya Shenoy

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Objective: To assess the effect of clinical parameters (bonding agent, preparation design & storage media) on the strength of reattached anterior tooth fragment. Methodology: This is a systematic review and meta-analysis for articles referred from MEDLINE, PUBMED, and GOOGLE SCHOLAR. The articles on tooth reattachment and clinical factors affecting fracture strength/bond strength/fracture resistance of the reattached tooth fragment in anterior teeth and published in English from 1999 to 2016 were included for final review. Results: Out of 120 shortlisted articles, 28 articles were included for the systematic review and meta-analysis based on 3 clinical parameters i.e. bonding agent, tooth preparation design & storage media. Forest plot & funnel plots were generated based on individual clinical parameter and their effect on strength of reattached anterior tooth fragment. Results based on analysis suggest combination of both conclusive evidence favoring the experimental group as well as in-conclusive evidence for individual parameter. Conclusion: There is limited evidence as there are fewer articles supporting each parameter in human teeth. Bonding agent had showed better outcome in selected studies.

Keywords: bonding agent, bond strength, fracture strength, preparation design, reattachment, storage media

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Authors: Ammani K., Glory M.

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Demands of traditional herbal medicines are increasing day by day over the world. Considering the growing demand of medicinal plants in curative treatments and the role of VAM fungi in augmentation of the production of active secondary metabolites by the medicinal plants, the present work has been undertaken to survey the mycorrhizal status in 30 different medicinal plants belonging to various families from Krishna district, Andhra Pradesh. The roots were collected carefully and stained by the Phillips & Hayman technique. Basing on the occurrence of vesicles and arbuscules, categorized into four grades; Excellent: mycelia, vesicles or arbuscules present more than 75% of root bits, Good: mycelia, vesicles or arbuscules present 50-75% in surface of root bits, moderate: mycelia, vesicles or arbuscules present 25-50% in surface of root bits, and poor: mycelia, vesicles or arbuscules present 1-25% in surface of root bits. The study reveals that the roots of all plants were colonized by AM fungi. Percentage of root colonization by AM fungi was more in Aloe vera, Phylanthus emblica, Azadiracta indica and least in plants such as Aerva lanata, Vinca rosea, Crotalaria verrucosa among the 30 medicinal plants in present study. The enhancement of growth and vigour and increased production of bioactive compounds of the medicinal plants is desirable which may be achieved by inoculation of the roots with Arbuscular mycorrhizal fungi. There is a steady increase in the cultivation of medicinal plants to maintain a steady supply to support the increasing demand but corresponding researches of VAM fungi and their association in medicinal plants have received very little attention as compared to the studies on forest species and field crops. So a vast research on this field is necessary for a better tomorrow.

Keywords: Arbuscular mycorrhizae, colonization, categories, medicinal plants

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Authors: Samir Chekchaki, ArifaBeddiar

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Nowadays, more and more species are introduced outside their natural range. If most of them remain difficult, some may adopt a much more dynamic behavior. Indeed, we have witnessed in recent decades, the development of high forests of Acacia mearnsii in El Kala National Park. Introduced indefinitely, this leguminous intended to make money (nitrogen supply for industrial plantations of Eucalyptus), became one of the most invasive and more costly in terms of forest management. It has crossed all barriers: it has acclimatized, naturalized and then expanded through diverse landscapes; entry into competition with native species such as cork oak and altered ecosystem functioning. Therefore, it is interesting to analyze this new threat by relying on plants as bio-indicator for assessing biodiversity at different scales. We have identified the species present in several plots distributed in a range of vegetation types subjected to different degrees of disturbance by using the braun-blanquet method. Fifty-six species have been recorded. They are distributed in 48 genera and 29 families. The analysis of the relative frequency of species correlated with relative abundance clearly shows that the Acacia mearnsii feels marginalized. The ecological analysis of this biological invasion shows that disruption of either natural or anthropogenic origin (fire, prolonged drought, cut) represent the factors that exacerbate invasion by opening invasion windows. The lifting of seeds of Acacia mearnsii lasting physical dormancy (and variable) is ensured by the thermal shock in relation to its heliophilous character.

Keywords: Acacia mearnsii De Wild, El Kala National park, fire, invasive, vegetation

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Authors: Khizar Samiullah Samiullah, Riffat Yasin, Khurrum Feroz, Omer Draz, Memmona Nazish

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New fossil remains of artiodactyl have been recovered from three Late Miocene localities, Lava, Dhok Bun Ameer Khatoon and Hasnoot. These localities belong to lower and middle Siwalik Hills of Pakistan, the Chinji and Dhok Pathan Formation respectively and are remarkably rich in fossils of artiodactyl. The fauna mainly comprises various families of order Artiodactyla; Cervidae, Equidea, Proboscidea, Giraffidea, Rhinocerotidae, Tragulidea, Suidae and Primates. In Chinji Formation Lava and Dhok Bun Ameer Khatoon are located in district Chakwal while in Upper Dhok Pathan Formation the best fossils exposure site is Hasnoot which is located in District Jhelum, Punjab, Pakistan. Specimens described and discussed here include right and left maxilla, isolated upper premolars and molars which have been collected during extensive fieldwork. After morphological and comparative analysis the collection is attributed to Giraffokeryx, Giraffa, Listriodon, Dorcatherium, Selenoportax and Pachyportax. In this study evolutionary status, taxonomy and biogeographical distribution as well as the relationship of different Artiodactyls have been discussed comprehensively. The Palaeoenvironmental studies reveal the persistence of mosaics of diverse habitats ranging from tropical evergreen forest to subtropical ones, closed seasonal woodlands to wooded savannas during the deposition of these outcrops.

Keywords: Artiodactyla, fossil dentition, late Miocene, lower and middle Siwaliks

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Authors: Jesica López, Deniz Koca, Asaf Tzachor

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In 2016 the historic peace accord between the Colombian government and the Revolutionary Armed Forces of Colombia (FARC) had no strong mechanism for managing changes to land use and the environment. Since the end of a 60-year conflict in Colombia, large areas of forest in the Amazon region have been rapidly converted to agricultural uses, most recently by cattle ranching. This suggests that the peace agreement presents a threat to the conservation of the country's rainforest. We analyze the effects of cattle ranching as a driver and accelerator of deforestation from a systemic perspective, focusing on two key leverage points the legal and illegal activities involved in the cattle ranching practices. We map and understand the inherent dynamic complexity of deforestation, including factors such as land policy instruments, national strategy to tackle deforestation, land use nexus with Amazonian food systems, and loss of biodiversity. Our results show that deforestation inside Colombian Protected Areas (PAs) in the Amazon region and the surrounding buffer areas has accelerated with the onset of peace. By using a systems analysis approach, we contextualized the competition of land between cattle ranching and the need to protect tropical forests and their biodiversity loss. We elaborate on future recommendations for land use management decisions making suggest the inclusion of an Amazonian food system, interconnecting and visualizing the synergies between sustainable development goals, climate action (SDG 13) and life on land (SDG 15).

Keywords: tropical rainforest, deforestation, sustainable land use, food security, Colombian Amazon

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Authors: Juliana C. Alencar, Monica Ferreira do Amaral Porto

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The blue-green infrastructure in recent years has been pointed out as a possibility to increase the environmental quality of watersheds. The regulation ecosystem services brought by these areas are many, such as the improvement of the air quality of the air, water, soil, microclimate, besides helping to control the peak flows and to promote the quality of life of the population. This study proposes a blue-green infrastructure scenario for the Jaguaré watershed, located in the western zone of the São Paulo city in Brazil. Based on the proposed scenario, it was verified the impact of the adoption of the blue and green infrastructure in the control of the peak flow of the basin, the benefits for the avifauna that are also reflected in the flora and finally, the quantification of the regulation ecosystem services brought by the adoption of the scenario proposed. A survey of existing green areas and potential areas for expansion and connection of these areas to form a network in the watershed was carried out. Based on this proposed new network of green areas, the peak flow for the proposed scenario was calculated with the help of software, ABC6. Finally, a survey of the ecosystem services contemplated in the proposed scenario was made. It was possible to conclude that the blue and green infrastructure would provide several regulation ecosystem services for the watershed, such as the control of the peak flow, the connection frame between the forest fragments that promoted the environmental enrichment of these fragments, improvement of the microclimate and the provision of leisure areas for the population.

Keywords: green and blue infrastructure, sustainable drainage, urban waters, ecosystem services

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Authors: Višnjica Vučetić, Mislav Anić, Jelena Bašić, Petra Sviličić, Ivana Tomašević

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The Agroclimatic Atlas of Croatia (Atlas) for the periods 1981–2010 and 1991–2020 is monograph of six chapters in digital form. Detailed descriptions of particular agroclimatological data are given in separate chapters as follows: agroclimatic indices based on air temperature (degree days, Huglin heliothermal index), soil temperature, water balance components (precipitation, potential evapotranspiration, actual evapotranspiration, soil moisture content, runoff, recharge and soil moisture loss) and fire weather indices. The last chapter is a description of the digital methods for the spatial interpolations (R and GIS). The Atlas comprises textual description of the relevant climate characteristic, maps of the spatial distribution of climatological elements at 109 stations (26 stations for soil temperature) and tables of the 30-year mean monthly, seasonal and annual values of climatological parameters at 24 stations. The Atlas was published in 2021, on the seventieth anniversary of the agrometeorology development at the Meteorological and Hydrological Service of Croatia. It is intended to support improvement of sustainable system of agricultural production and forest protection from fire and as a rich source of information for agronomic and forestry experts, but also for the decision-making bodies to use it for the development of strategic plans.

Keywords: agrometeorology, agroclimatic indices, soil temperature, water balance components, fire weather index, meteorological and hydrological service of Croatia

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Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

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Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

Procedia PDF Downloads 50

Authors: Filippo Ranalli, Forest Flager, Martin Fischer

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This paper presents a ground structure method to optimize the topology and discrete member sizing of steel frame structures in order to minimize total installed cost, including material, fabrication and erection components. The proposed method improves upon existing cost-based ground structure methods by incorporating constructability considerations well as satisfying both strength and serviceability constraints. The architecture for the method is a bi-level Multidisciplinary Feasible (MDF) architecture in which the discrete member sizing optimization is nested within the topology optimization process. For each structural topology generated, the sizing optimization process seek to find a set of discrete member sizes that result in the lowest total installed cost while satisfying strength (member utilization) and serviceability (node deflection and story drift) criteria. To accurately assess cost, the connection details for the structure are generated automatically using accurate site-specific cost information obtained directly from fabricators and erectors. Member continuity rules are also applied to each node in the structure to improve constructability. The proposed optimization method is benchmarked against conventional weight-based ground structure optimization methods resulting in an average cost savings of up to 30% with comparable computational efficiency.

Keywords: cost-based structural optimization, cost-based topology and sizing, optimization, steel frame ground structure optimization, multidisciplinary optimization of steel structures

Procedia PDF Downloads 316

Authors: Md. Kamrul Hassan, Ari Pappinen

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Wood energy is the single most important form of renewable energy in many parts of the world especially in the least developing countries in South Asia like Bangladesh. The last portion of the national population of this country depends on wood energy for their daily primary energy need. This paper deals with the estimation of wood fuel at the current level and identifies the challenges and strategies related to the development of this resource. Desk research, interactive research and field survey were conducted for gathering and analyzing of data for this study. The study revealed that wood fuel plays a significant role in total primary energy supply in Bangladesh, and the contribution of wood fuel in final energy consumption in 2013 was about 24%. Trees on homestead areas, secondary plantation on off forest lands, and forests are the main sources of supplying wood fuel in the country. Insufficient supply of wood fuel against high upward demand is the main cause of concern for sustainable consumption, which eventually leads deterioration and depletion of the resources. Inadequate afforestation programme, lack of initiatives towards the utilization of set-aside lands for wood energy plantations, and inefficient management of the existing resources have been identified as the major impediments to the development of wood energy in Bangladesh. The study argued that enhancement of public-private-partnership afforestation programmes, intensifying the waste and marginal lands with short-rotation tree species, and formulation of biomass-based rural energy strategies at the regional level are relevant to the promotion of sustainable wood energy in the country.

Keywords: Bangladesh, challenge, supply, wood energy

Procedia PDF Downloads 165

Authors: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

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A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme gradient boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impair, multiclass classification, ADNI, support vector machine, random forest

Procedia PDF Downloads 160

Authors: Arthur Rouanet, Marina Gavaldao

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Throughout the second half of the 20th Century, estimates indicate that soil losses due to erosion have impacted one-third of worldwide arable lands. As such, these losses are amongst the largest threats to agriculture sustainability and production potential. Increasing tree cover is considered one of the most efficient methods to mitigate this phenomenon. The present study describes soil erosion measurements in different land cover situations in Alto Huayabamba, Peru, using the experimental plot methodology. Three parcels were studied during a one-year period (starting September 2015) with 3 different land cover scenarii evaluated: 10-year-old secondary tropical forest (P1), 3-year-old native species reforestation (P2) and bare soil (P3). Information was collected systematically after each rain to assess the average rainfall, water runoff and soil eroded. The results indicate that variance in land cover has a strong impact on the level of soil erosion. In our study, it was found that P1, P2 and P3 had erosion rates of 92 kg/ha/yr, 11 tons/ha/yr and 59,7 tons/ha/year respectively. Using a replacement cost method, the potential of limiting erosion by reforesting bare soil was estimated to be 561 $/ha/yr after three years and 687 $/ha/yr after ten years. Finally, the results of the study allow us to assess the potential soil services provided by vegetation, which could be an important building block for a payment for ecosystems services (PES) scheme. The latter has been increasingly spread all over the world through Public-Private Partnerships (PPP).

Keywords: agroforestry, erosion, ecosystem services, payment for ecosystem services (PES), water conservation, public private partnership (PPP)

Procedia PDF Downloads 231

Authors: M. Sanjarani, A. Danehkar, A. Mashincheyan, A. H. Javid, S. M. R. Fatemi

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The oil spill in marine water has direct impact on coastal resources and community. Environmental Sensitivity Index (ESI) map is the first step to assess the potential impact of an oil spill and minimize the damage of coastal resources. In order to create Environmental Sensitivity Maps for the Chabahar bay (Iran), information has been collected in three different layers (Shoreline Classification, Biological and Human- uses resources) by means of field observations and measurements of beach morphology, personal interviews with professionals of different areas and the collection of bibliographic information. In this paper an attempt made to prepare an ESI map for sensitivity to oil spills of Chabahar bay coast. The Chabahar bay is subjected to high threaten to oil spill because of port, dense mangrove forest,only coral spot in Oman Sea and many industrial activities. Mapping the coastal resources, shoreline and coastal structures was carried out using Satellite images and GIS technology. The coastal features classified into three major categories as: Shoreline Classification, Biological and Human uses resources. The important resources classified into mangrove, Exposed tidal flats, sandy beach, etc. The sensitivity of shore was ranked as low to high (1 = low sensitivity,10 = high sensitivity) based on geomorphology of Chabahar bay coast using NOAA standards (sensitivity to oil, ease of clean up, etc). Eight ESI types were found in the area namely; ESI 1A, 1C, 3A, 6B, 7, 8B,9A and 10D. Therefore, in the study area, 50% were defined as High sensitivity, less than 1% as Medium, and 49% as low sensitivity areas. The ESI maps are useful to the oil spill responders, coastal managers and contingency planners. The overall ESI mapping product can provide a valuable management tool not only for oil spill response but for better integrated coastal zone management.

Keywords: ESI, oil spill, GIS, Chabahar Bay, Iran

Procedia PDF Downloads 333

Authors: Wendu Admasu, Assefa Sintayehu, Alemu Gezahgne, Zewdu Terefework

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Eucalyptus is the most widely planted forest tree species in the world. In Ethiopia, pathogenic fungi pose an increasing threat to Eucalyptus species. Due to limited research, there is insufficient information on the associated diseases and pathogens. This study investigated Eucalyptus diseases, the extent of their damage, and the causal fungal pathogens. A Eucalyptus disease survey was conducted in the Eucalyptus forestry areas of Ethiopia during the growth years 2019/20 and 2020/21. Disease assessment and sampling were carried out in eighteen plantations at nine locations. E. camaldulensis was the most dominant species planted in the surveyed areas. The field study shows a high incidence and severity of canker diseases. Diseased stem and branch samples were collected, cultured on malt extract agar media and studied. The results of morphological and ITS sequence analysis confirmed that the fungal species Neofusicoccum parvum, Lasiodiplodia theobromae, and Aplosporella hesperidica caused the observed canker symptoms. This is the first report of Lasiodiplodia theobromae and Aplosporella hesperidica causing diseases in Eucalyptus plants in Ethiopia. Changes in global climate and environmental factors, such as altitude, are believed to have a strong impact on the susceptibility of Eucalyptus plants to diseases. Strict quarantine practices and continuous monitoring of pathogenic and endophytic fungal species associated with Eucalyptus trees are issued to be prioritized to effectively control and manage the disease.

Keywords: Neofusicoccum, Lasiodiplodia, Aplosporella, pathogenicity, phylogeny, severity

Procedia PDF Downloads 30