Search results for: tree species

Authors: K. S. Parlak, E. Turan

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The separation of marbles according to the pattern quality is a process made according to expert decision. The classification phase is the most critical part in terms of economic value. In this study, a self-learning system is proposed which performs the classification of marbles quickly and with high success. This system performs ten feature extraction by taking ten marble images from the camera. The marbles are classified by decision tree method using the obtained properties. The user forms the training set by training the system at the marble classification stage. The system evolves itself in every marble image that is classified. The aim of the proposed system is to minimize the error caused by the person performing the classification and achieve it quickly.

Keywords: decision tree, feature extraction, k-means clustering, marble classification

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Authors: Bhojan Dhakal, Naba Raj Devkota, Chet Raj Upreti, Maheshwar Sapkota

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A study was conducted to find out the production potential, nutrient composition, and the variability of the most commonly available fodder trees along with the varying altitude to help optimize the dry matter requirement during winter lean period. The study was carried out from March to June, 2012 in Lho and Prok Village Development Committee of Manaslu Conservation Area (MCA), located in Gorkha district of Nepal. The other objective of the research was to learn the impact of climate change on livestock production linking it with feed availability. The study was conducted in two parts: social and biological. Accordingly, a households (HHs) survey was conducted to collect primary data from 70 HHs, focusing on the perception of respondents on impacts of climatic variability on the feeding management. The next part consisted of understanding yield potential and nutrient composition of the four most commonly available fodder trees (M. azedirach, M. alba, F. roxburghii, F. nemoralis), within two altitudes range: (1500-2000 masl and 2000-2500 masl) by using a RCB design in 2*4 factorial combination of treatments, each replicated four times. Results revealed that majority of the farmers perceived the change in climatic phenomenon more severely within the past five years. Farmers were using different adaptation technologies such as collection of forage from jungle, reducing unproductive animals, fodder trees utilization, and crop by product feeding at feed scarcity period. Ranking of the different fodder trees on the basis of indigenous knowledge and experiences revealed that F. roxburghii was the best-preferred fodder tree species (index value 0.72) in terms overall preferability whereas M. azedirach had highest growth and productivity (index value 0.77), F. roxburghii had highest adoptability (index value 0.69) and palatability (index value 0.69) as well. Similarly, fresh yield and dry matter yield of the each fodder trees was significant (P < 0.01) between the altitude and within species. Fodder trees yield analysis revealed that the highest dry matter (DM) yield (28 kg/tree) was obtained for F. roxburghii but that remained statistically similar (P > 0.05) to the other treatment. On the other hand, most of the parameters: ether extract (EE), acid detergent lignin (ADL), acid detergent fibre (ADF), cell wall digestibility (CWD), relative digestibility (RD), digestible nutrient (TDN), and Calcium (Ca) among the treatments were highly significant (P < 0.01). This indicates the scope of introducing productive and nutritive fodder trees species even at the high altitude to help reduce fodder scarcity problem during winter. The finding also revealed the scope of promoting all available local fodder trees species as crude protein content of these species were similar.

Keywords: fodder trees, yield potential, climate change, nutrient composition

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Authors: Dhanuj M. Gandikota

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Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.

Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry

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Authors: Somayeh Akrami, Vali-Allah Mozaffarian, Habib Onsori

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The studied region in this research, watershed Kuhkamar river, is about 112.66 square kilometers, it is located between 45º 48' 9" to 45º 2' 20" N and 38º 34' 15" to 38º 40' 28" E. The gained results of the studies on flora combinations, proved 287 plant species in 190 genera and 51 families. Asteracea with 49 and Lamiaceae with 27 plant species are the major plant families. Among collected species one interesting plant was found and determined as a new record Anemone narcissiflora L. for flora of Iran. This plant is known as a complex species that shows intraspecific speciation and is classified into about 12 subspecies and 10 varieties in world. To identify the infraspecies taxons of this species, in addition to morphological characteristics, the use of appropriate molecular markers for the better isolation of the individuals were needed.

Keywords: Anemone narcissiflora, floristic Study, kuhkamar, molecular marker

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Authors: Nur Amira nor Arifin, Tashia Marie Anthony, Mohd Ruzlin Mokhtar, Huzainie Shafi Abd Halim

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Cross-linked polyethylene (XLPE) material is being used as the cable insulation for the past decades due to its higher working temperature of 90 ˚C and some other advantages. However, the use of XLPE as an insulating material for underground distribution cables may have subjected to the unforeseeable weather and uncontrollable environmental condition. These unfavorable condition when combine with high electric field may lead to the initiation and growth of water tree in XLPE insulation. There are several studies on numerous nanofillers incorporate into polymer matrix to hinder the growth of tree propagation. Hence, in this study aims to investigate the effect of MgO and rubber nanofillers at different concentration on the electrical tree of XLPE. The nanofillers and XLPE were mixed and later extruded. After extrusion, the material were then fabricated into the desired shape for experimental purposes. The result shows that the electrical tree propagation of XLPE filled with optimize concentration of nanofillers were much slower compared to pure XLPE. In this paper, the effect of nanofillers towards electrical treeing characteristic will be discussed.

Keywords: electrical trees, nanofillers, polymer nanocomposites, XLPE

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Mayuri Roy Choudhury

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In recent times the concept of agrivoltaics has gained popularity due to the dual use of land and the added value provided by photovoltaics in terms of renewable energy and crop production on farms. However, the transition towards agrivoltaics has been slow, and our research tries to investigate the obstacles leading towards the slow progress of agrivoltaics. We applied data science decision tree algorithms to quantify qualitative perceptions of farmers in the United States for agrivoltaics. To date, there has not been much research that mentions farmers' perceptions, as most of the research focuses on the benefits of agrivoltaics. Our study adds value by putting forward the voices of farmers, which play a crucial towards the transition to agrivoltaics in the future. Our results show a mixture of responses in favor of agrivoltaics. Furthermore, it also portrays significant concerns of farmers, which is useful for decision-makers when it comes to formulating policies for agrivoltaics.

Keywords: agrivoltaics, decision-tree algorithms, farmers perception, transition

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Authors: Manar Makhoul, Buthainah Alsalamah, Salam Lawand, Hassan Azzam

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The major storage proteins in endosperm of 33 cultivated and wild barley genotypes (H.vulgare, H. spontaneum, H. bulbosum, H. murinum, H. marinum) were analyzed to demonstrate the variation in the hordein polypeptides encoded by multigene families in grains. The SDS-PAGE revealed 13 and 17 alleles at the Hor1 and the Hor2 loci respectively, with frequencies from 0.83 to 14 and 0.56 to 13.41% respectively, while seven alleles at the Hor3 locus with frequencies from 3.63 to 30.91% were recognized. The phylogenetic analysis indicated to relevance of the polymorphism in hordein patterns as successful tool in identifying the individual genotypes and discriminating the species according to genome type. We also reported in this research complete nucleotide sequence B-hordein genes of seven wild and cultivated barley genotypes. A 152bp upstream sequence of B-hordein promoter contained a TATA box, CATC box, AAAG motif, N-motif and E-motif. In silico analysis of B-Hordein sequences demonstrated that the coding regions were not interrupted by any intron, and included the complete ORF which varied between 882 and 906 bp, and encoded mature proteins with 293-301 residues characterized by high contents of glutamine (29%), and proline (18%). Comparison of the predicted polypeptide sequences with the published ones suggested that all S-rich prolamins genes are descended from common ancestor. The sequence started at N-terminal with a signal peptide, and then followed directly by two domains; a repetitive one based on the repetition of the repeat unit PQQPFPQQ and C-terminal domain. Also, it was found that positions of the eight cysteine residues were highly conserved in all the B-hordein sequences, but Hordeum bulbosum had additional unpaired one. The phylogenetic tree of B-hordein polypeptide separated the genotypes in distinct seven subgroups. In general, the high homology between B-hordeins and LMW glutenin subunits suggests similar bread-making influences for these B-hordeins.

Keywords: hordeum, phylogenetic tree, sequencing, storage protein

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Authors: Sami Michael Ayodele

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Cordyceps are members of the fungi family Cordycepitaceae which are formally in Clavicipitaceae. They parasitize the larvae and adults of different susceptible arthropods. They are highly priced and have been reported to be highly medicinal. Cordyceps have been used for centuries in traditional medicine in China and other Asian countries. Survey studies were carried out to determine the presence of Cordyceps and another entomopathogenic fungal floral in North Central Nigeria for two consecutive years. Thirty samples were collected, twenty-eight were identified, and two were unidentified. Most identified species belong to Ophiocordyceps species (20samples), Cordyceps species (4samples) and Isaria species (4samples). The species identified were: Cordyceps pseudomilitaris, Cordyceps tuberculata, Cordyceps cylindrical, Ophiocordyceps nutans, O. criminals, O. oxycephala, O. kniphofioides and Isaria sinclairii. The morphological and microscopic features of the collected and identified species were similar to those reported in other countries. This is the first official report on the presence of Cordyceps species in Nigeria. Further collections from different ecological regions of Nigeria will show the richness of the floral diversity of these entomopathogenic and medicinal mushrooms in Nigeria.

Keywords: cordyceps, entomopathogenic, medicinal, North Central, Nigeria

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Authors: Michaela Chovancova, Pavel Niedoba

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For the treatment of acute and chronic lung diseases it is preferred to deliver medicaments by inhalation. The drug is delivered directly to tracheobronchial tree. This way allows the given medicament to get directly into the place of action and it makes rapid onset of action and maximum efficiency. The transport of aerosol particles in the particular part of the lung is influenced by their size, anatomy of the lungs, breathing pattern and airway resistance. This article deals with calculation of airway resistance in the lung model of Horsfield. It solves the problem of determination of the pressure losses in bifurcation and thus defines the pressure drop at a given location in the bronchial tree. The obtained data will be used as boundary conditions for transport of aerosol particles in a central part of bronchial tree realized by Computational Fluid Dynamics (CFD) approach. The results obtained from CFD simulation will allow us to provide information on the required particle size and optimal inhalation technique for particle transport into particular part of the lung.

Keywords: human lungs, bronchial tree, pressure losses, airways resistance, flow, breathing

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Authors: Nasreen Jeelani, Huining Shi , Di An, Lu Xia, Shuqing An

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Heavy metals contamination in aquatic ecosystem is a major environmental problem since its accumulation along the food chain pose public health risk. The concentration of heavy metals (Cd, Cr, Cu, Ni, Pb and Zn) in soil and plants species collected from different streams of Suoxu River, China was investigated. This aim was to define the level of pollutants in Suoxu River, find which plant species exhibits the greatest accumulation and to evaluate whether these species could be useful for phytoremediation. While total soil Cd, Cr, Cu, Ni, Pb, and Zn concentrations varied, respectively, from 0.09 to 0.23 , 58.6 to 98, 9.72 to 80.5, 15.3 to 41, 15.2 to 27.3 and 35 to 156 (mg-kg-1), those in plants ranged from 0.035 to 0.49, 2.91 to 75.6, 4.79 to 32.4, 1.27 to 16.1, 0.62 to10.2, 18.9 to 84.6 (mg-kg-1), respectively. Based on BCFs and TFs values, most of the studied species have potential for phytostabilization. The plants with most effective in the accumulation of metals in shoots are Phragmatis australis (TF=2.29) and Iris tectorum (TF =2.07) for Pb. While Chenopodium album, (BCF =3.55), Ranunculus sceleratus, (BCF= 3.0), Polygonum hydropiper (BCF =2.46) for Cd and Iris tectorum (BCF=2.0) for Cu was suitable for phytostabilization. Among the plant species screened for Cd, Cr, Cu, Ni, Pb and Zn, most of the species were efficient to take up more than one heavy metal in roots. Our study showed that the native plant species growing on contaminated sites may have the potential uses for phytoremediation.

Keywords: heavy metals, huaihe river catchments, sediment, plants

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Authors: Miguel Mellado, Cecilia Zapata

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Goats can be exploited in harsh environments due to their capacity to adjust to limited quantity and quality forage sources. In these environments, leguminous trees can be used as supplementary feeds as foliage and fruits of these trees can contribute to maintain or improve production efficiency in ruminants. The objective of this study was to determine the nutritional value of three leguminous trees heavily selected by goats in a xerophyllous shrubland. Chemical composition and in vitro dry matter disappearance (IVDMD) of leaves and pods from leucaena (Leucaena leucocephala), mesquite (Prosopis laevigata) and huisache (Acacia farnesiana) is presented. Crude protein (CP) ranged from 17.3% for leaves of huisache to 21.9% for leucaena. The neutral detergent fiber (NDF) content ranged from 39.0 to 40.3 with no difference among fodder threes. Across tree species, mean IVDMD was 61.6% for pods and 52.2% for leaves. IVDMD for leaves was highest (P < 0.01) for leucaena (54.9%) and lowest for huisache (47.3%). Condensed tannins in an acetonic extract were highest for leaves of huisache (45.3 mg CE/g DM) and lowest for mesquite (25.9 mg CE/g DM). Pods and leaves of huisache presented the highest number of secondary metabolites, mainly related to hydrobenzoic acid and flavonols; leucaena and mesquite presented mainly flavonols and anthocyanins. It was concluded that leaves and pods of leucaena, mesquite and huisache constitute valuable forages for ruminant livestock due to its low fiber, high CP levels, moderate in vitro fermentation characteristics and high mineral content. Keywords: Fodder tree; ruminants; secondary metabolites; minerals; tannins

Keywords: fodder tree, ruminants, secondary metabolites, minerals, tannins

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Authors: L. Salomon, P. Sklenar

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The Andes hold the highest plant species diversity in the world. How this occurred is one of the most intriguing questions in studies addressing the origin and patterning of plant diversity worldwide. Recently, the explosive adaptive radiations found in high Andean groups have been pointed as triggers to this spectacular diversity. The Andes is the species-richest area for the biggest genus from the Asteraceae family: Senecio. There, the genus presents an incredible diversity of species, striking growth form variation, and large niche span. Even when some studies tried to disentangle the evolutionary story for some Andean species in Senecio, they obtained partially resolved and low supported phylogenies, as expected for recently radiated groups. The high-throughput sequencing (HTS) approaches have proved to be a powerful tool answering phylogenetic questions in those groups whose evolutionary stories are recent and traditional techniques like Sanger sequencing are not informative enough. Although these tools have been used to understand the evolution of an increasing number of Andean groups, nowadays, their scope has not been applied for Senecio. This project aims to contribute to a better knowledge of the mechanisms shaping the hyper diversity of Senecio in the Andean region, using HTS focusing on Senecio ser. Culcitium (Asteraceae), recently recircumscribed. Firstly, reconstructing a highly resolved and supported phylogeny, and after assessing the role of allopatric differentiation, hybridization, and genome duplication in the diversification of the group. Using the Hyb-Seq approach, combining target enrichment using Asteraceae COS loci baits and genome skimming, more than 100 new accessions were generated. HybPhyloMaker and HybPiper pipelines were used for the phylogenetic analyses, and another pipeline in development (Paralogue Wizard) was used to deal with paralogues. RAxML was used to generate gene trees and Astral for species tree reconstruction. Phyparts were used to explore as first step of gene tree discordance along the clades. Fully resolved with moderated supported trees were obtained, showing Senecio ser. Culcitium as monophyletic. Within the group, some species formed well-supported clades with morphologically related species, while some species would not have exclusive ancestry, in concordance with previous studies using amplified fragment length polymorphism (AFLP) showing geographical differentiation. Discordance between gene trees was detected. Paralogues were detected for many loci, indicating possible genome duplications; ploidy level estimation using flow cytometry will be carried out during the next months in order to identify the role of this process in the diversification of the group. Likewise, TreeSetViz package for Mesquite, hierarchical likelihood ratio congruence test using Concaterpillar, and Procrustean Approach to Cophylogeny (PACo), will be used to evaluate the congruence among different inheritance patterns. In order to evaluate the influence of hybridization and Incomplete Lineage Sorting (ILS) in each resultant clade from the phylogeny, Joly et al.'s 2009 method in a coalescent scenario and Paterson’s D-statistic will be performed. Even when the main discordance sources between gene trees were not explored in detail yet, the data show that at least to some degree, processes such as genome duplication, hybridization, and/or ILS could be involved in the evolution of the group.

Keywords: adaptive radiations, Andes, genome duplication, hybridization, Senecio

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

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Authors: Hilal Bulut, Serap Saler

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Protozoan ciliate epibionts infestation on zooplankton in Cip Dam Lake were studied seasonally, between spring 2014-winter 2015 The ciliates peritrich Epibiont Epistylis sp. (Protozoa, Ciliophora) was found as colony form on some individuals of different zooplanktonic groups, especially rotifers and copepods. Totally 23 zooplankton species (19 species from Rotifera, 3 species from Cladocera and 1 species from Copepoda in Cip Dam Lake were investigated. Rotifers were the most important zooplanktonic group (82.7 % of total) and the taxa observed with epibionts were Keratella, Polyarthra, and Brachionus. The highest densities of infected zooplankton was observed in winter (14265 ind.m-3), the lowest densities of infected zooplankton was found in summer (3056 ind.m-). Rotifers were most infected groups with 75% in this study. Epistylis sp. was found on three species of rotifers and one copepod species. Infestation of Epistylis sp. has been registered for the first time in Cip Dam Lake.

Keywords: copepoda, epibiosis, peritrich, rotifera

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Authors: Oluwafemi Samuel Oyamakin

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The forest in Nigeria is currently estimated to extend to around 9.6 million hectares, but used to expand over central and southern Nigeria decades ago. The forest estate is shrinking due to long-term human exploitation for agricultural development, fuel wood demand, uncontrolled forest harvesting and urbanization, amongst other factors, compounded by population growth in rural areas. Nigeria has lost more than 50% of its forest cover since 1990 and currently less than 10% of the country is forested. The current deforestation rate is estimated at 3.7%, which is one of the highest in the world. Reducing Emissions from Deforestation and forest Degradation plus conservation, sustainable management of forests and enhancement of forest carbon stocks constituted what is referred to as REDD+. This study evaluated some of the existing way of computing carbon stocks using eight indigenous tree species like Mansonia, Shorea, Bombax, Terminalia superba, Khaya grandifolia, Khaya senegalenses, Pines and Gmelina arborea. While these components are the essential elements of REDD+ programme, they can be brought under a broader framework of systems analysis designed to arrive at optimal solutions for future predictions through statistical distribution pattern of carbon sequestrated by various species of tree. Available data on height and diameter of trees in Ibadan were studied and their respective potentials of carbon sequestration level were assessed and subjected to tests so as to determine the best statistical distribution that would describe the carbon sequestration pattern of trees. The result of this study suggests a reasonable statistical distribution for carbons sequestered in simulation studies and hence, allow planners and government in determining resources forecast for sustainable development especially where experiments with real-life systems are infeasible. Sustainable management of forest can then be achieved by projecting future condition of forests under different management regimes thereby supporting conservation and REDD+ programmes in Nigeria.

Keywords: REDD+, carbon, climate change, height and diameter

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Authors: F. O. Oboite, P. G. Comeau

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Advance regeneration is present in many lodgepole pine stands in Alberta. When the overstory pine canopy is killed by Mountain Pine Beetle (MPB) the growth of this advance is likely to increase. Understanding the growth response of these understory tree species is needed to improve mid-term timber supply projections and management decisions. To quantify the growth (diameter, height, height/diameter ratio) responses of black spruce and white spruce to lodgepole pine mortality, sample trees of black and white spruce advance regeneration were selected from 7 lodgepole pine dominated stands (5 attacked; 2 control) in the Foothills Region of western Alberta. Measurements were collected 7-8 years after MPB attack across a wide range of spruce height and stand densities. Analysis was done using mixed model linear regression. Result indicates that there was an increase in both diameter and height growth after MPB attack; however, this increase in growth was delayed for about four years. Both spruce species had similar height response and their height/diameter ratio decreased after release, partly as a result of increased understory light associated with loss of needles in the pine canopy. In addition, the diameter and height growth responses of both spruce species were strongly related to density, prerelease growth and initial size.

Keywords: mountain pine beetle, forest regeneration, lodgepole pine, growth response

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Authors: Rosario Rivera Rubite, Ching-I Peng, Che-Wei Lin, Mark Hughes, Yoshiko Kono, Kuo-Fang Chung

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The flora of Panay Island is under-collected compared with the other islands of the Philippines. In a joint expedition to the island, botanists from Taiwan and the Philippines found three unknown Begonia and compared them with potentially allied species. The three species are clearly assignable to Begonia section Baryandra which is largely endemic to the Philippines. Studies of literature, herbarium specimens, and living plants support the recognition of the three new species: Begonia culasiensis, Begonia merrilliana, and Begonia sykakiengii. Somatic chromosomes at metaphase were determined to be 2n=30 for B. culasiensis and 2n=28 for both B. merrilliana and B. sykakiengii, which are congruent with those of most species in sect. Baryandra. Molecular phylogenetic evidence is consistent with B. culasiensis being a relict from the late Miocene, and with B. merrilliana and B. sykakiengii being younger species of Pleistocene origin. The continuing discovery of endemic Philippine species means the remaining fragments of both primary and secondary native vegetation in the archipelago are of increasing value in terms of natural capital. A secure future for the species could be realized through ex-situ conservation collections and raising awareness with community groups.

Keywords: conservation, endemic , herbarium , limestone, phylogenetics, taxonomy

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Authors: Soon-Mi Park, Ihn Sook Jeong

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This retrospective study was aimed to identify risk factors of intravenous (IV) infiltration for hospitalized children. The participants were 1,174 children for test and 424 children for validation, who admitted to a general hospital, received peripheral intravenous injection therapy at least once and had complete records. Data were analyzed with frequency and percentage or mean and standard deviation were calculated, and decision tree analysis was used to screen for the most important risk factors for IV infiltration for hospitalized children. The decision tree analysis showed that the most important traditional risk factors for IV infiltration were the use of ampicillin/sulbactam, IV insertion site (lower extremities), and medical department (internal medicine) both in the test sample and validation sample. The correct classification was 92.2% in the test sample and 90.1% in the validation sample. More careful attention should be made to patients who are administered ampicillin/sulbactam, have IV site in lower extremities and have internal medical problems to prevent or detect infiltration occurrence.

Keywords: decision tree analysis, intravenous infiltration, child, validation

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Authors: Kristýna Weissová

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This study is focused on two selected model taxa of invertebrates - Hymenoptera: Aculeata and Lepidopterawithnocturnalactivity, recordedatthesitesof lignite dumps and their surroundings in the North Bohemian Lignite Basin, Czech Republic. There search was conducted on 10 landfills, 3 study areas were determined on each landfill - primary and secondary succession and recultivation. A total of 3,202 individuals belonging to 232 species and 17 families of sagebrushinsects were collected. died, 74%of the species occurred on the primary succes sionare as, that is 2x more species than on the reclaimed areas. Of the total number of species and on all areas, 60 rare species were recorded - 29 vulnerable, 21 endangered, 8 critically endangered, and 2 extinct The areas of primary succession were again confirmed to be the richest in terms of rare species, hosting 39 rare species of Hymenoptera: Aculeata. In addition, bothextinct species were represented only on plots of primary succession. The family Crabronidae had the largestre presentation of species on theareasofleft primary succession, the family Halictidae was the most represented on the reclaimed areas and areas of secondary succession. A total of 3,634 moths were collected, assigned to 262 species and 10 families. A similar number of species occurred on the primary succession and reclaimed areas, but the reclaimed area had a greater abundance. Secondary successionsiteshostedha lf as many species and alsocontainedlow abundance compared to other management types. The results show that there claimed areas host a numerically larger group and more species of moths than the successionalareas. Rare species did not occur at any site. A higher number of days in locations without water bodies, wetland vegetation, and locations with a highre presentation of woody species. It is advisable to combine individual types of landscape management in such a way as to create a colorfulmosaic that supports biodiversity. In particular, we recommend incorporating natural successionintoreclamation plans, which is a refuge for many rare species of invertebrates, which has not yetbeenroutinely and purposefully practiced.

Keywords: hymenoptera: aculeata, lepidoptera, reclamation, succession, post-mining ara

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Authors: Serdar Yaman, Hanzade Haykiri-Acma

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Biomass is a CO₂-neutral fuel that is renewable and sustainable along with having very huge global potential. Efficient use of biomass in power generation and production of biomass-based biofuels can mitigate the greenhouse gasses (GHG) and reduce dependency on fossil fuels. There are also other beneficial effects of biomass energy use such as employment creation and pollutant reduction. However, most of the biomass materials are not capable of competing with fossil fuels in terms of energy content. High moisture content and high volatile matter yields of biomass make it low calorific fuel, and it is very significant concern over fossil fuels. Besides, the density of biomass is generally low, and it brings difficulty in transportation and storage. These negative aspects of biomass can be overcome by thermal pretreatments that upgrade the fuel property of biomass. That is, torrefaction is such a thermal process in which biomass is heated up to 300ºC under non-oxidizing conditions to avoid burning of the material. The treated biomass is called as biochar that has considerably lower contents of moisture, volatile matter, and oxygen compared to the parent biomass. Accordingly, carbon content and the calorific value of biochar increase to the level which is comparable with that of coal. Moreover, hydrophilic nature of untreated biomass that leads decay in the structure is mostly eliminated, and the surface properties of biochar turn into hydrophobic character upon torrefaction. In order to investigate the effectiveness of torrefaction process on biomass properties, several biomass species such as olive milling residue (OMR), Rhododendron (small shrubby tree with bell-shaped flowers), and ash tree (timber tree) were chosen. The fuel properties of these biomasses were analyzed through proximate and ultimate analyses as well as higher heating value (HHV) determination. For this, samples were first chopped and ground to a particle size lower than 250 µm. Then, samples were subjected to torrefaction in a horizontal tube furnace by heating from ambient up to temperatures of 200, 250, and 300ºC at a heating rate of 10ºC/min. The biochars obtained from this process were also tested by the methods applied to the parent biomass species. Improvement in the fuel properties was interpreted. That is, increasing torrefaction temperature led to regular increases in the HHV in OMR, and the highest HHV (6065 kcal/kg) was gained at 300ºC. Whereas, torrefaction at 250ºC was seen optimum for Rhododendron and ash tree since torrefaction at 300ºC had a detrimental effect on HHV. On the other hand, the increase in carbon contents and reduction in oxygen contents were determined. Burning characteristics of the biochars were also studied using thermal analysis technique. For this purpose, TA Instruments SDT Q600 model thermal analyzer was used and the thermogravimetric analysis (TGA), derivative thermogravimetry (DTG), differential scanning calorimetry (DSC), and differential thermal analysis (DTA) curves were compared and interpreted. It was concluded that torrefaction is an efficient method to upgrade the fuel properties of biomass and the biochars from which have superior characteristics compared to the parent biomasses.

Keywords: biochar, biomass, fuel upgrade, torrefaction

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Authors: Quynhan Tran, Hong Fan, Quockhanh Pham

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Automatic map generalization is a well-known problem in cartography. The development of map generalization research accompanied the development of cartography. The traditional map is plotted manually by cartographic experts. The paper studies none-scale automation generalization of resident polygons and house marker symbol, proposes methodology to evaluate the result maps based on minimal spanning tree. In this paper, the minimal spanning tree before and after map generalization is compared to evaluate whether the generalization result maintain the geographical distribution of features. The minimal spanning tree in vector format is firstly converted into a raster format and the grid size is 2mm (distance on the map). The statistical number of matching grid before and after map generalization and the ratio of overlapping grid to the total grids is calculated. Evaluation experiments are conduct to verify the results. Experiments show that this methodology can give an objective evaluation for the feature distribution and give specialist an hand while they evaluate result maps of none-scale automation generalization with their eyes.

Keywords: automatic cartography generalization, evaluation model, geographic feature distribution, minimal spanning tree

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Authors: Hong Li, Tingxian Li, Xudong Wang, Fengliang Zhao

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Unreliable flowering of chilling-required longan (Dimocarpus longan) due to increased air-temperatures have been the common concerns in the tropical areas. Our objectives were to assess the efficiency of chemicals in longan tree flowering and bearing using Growing Degree Days (GDD). The 2-year study was contacted in the tropical Haihan Island during 2012-2013. At pruning (August) the GDD values were started to count. The KClO3 treatments were applied to the root zones under the canopies at GDD 1300ºC while KH2PO4 rates were applied to the leaves at fruit setting at GDD 3000ºC and GDD 4000ºC. The results showed that total cumulative GDD was 6050ºC for longan. The GDD-guided KClO3 applications induced significant tree budding and flowering. The GDD-guided KH2PO4 applications stimulated higher leaf photosynthesis, carbonxylation efficiency, marketable fruit yield and quality (K+ and sugar) (P<0.05). It was concluded that the GDD-based model could efficiently support longan reliable flowering and bearing.

Keywords: canopy nutrition, flowering induction, growing degree days, longan, oxidant KClO3, tree physiology

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Authors: K. Umbleja, M. Ichino, H. Yaguchi

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In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

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Authors: Raees Khan, Mir A. Khan, Sheikh Z. Ul Abidin, Abdul S. Mumtaz

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In the present study, phytogeography and conservation status of gymnosperms of Pakistan were investigated. 44 gymnosperms species of 18 genera and 9 families were collected from 66 districts of the country. Among the 44 species, 20 species were native (wild) and 24 species were exotic (cultivated). Ephedra sarocarpa of Ephedraceae was not collected in this study from its distribution area and most probably it may be Nationally Extinct now from this area. Previously in Gymnosperms Flora of Pakistan 34 species was reported. 12 new gymnosperms species were recorded for the first time. Pinus wallichiana (40 districts), Cedrus deodara (39 districts) Pinus roxburghii (36 districts), Picea smithiana (36 districts) and Abies pindrow (34 districts) have the maximum ecological amplitude. Juniperus communis (17districts) and Juniperus excelsa (14 districts) were the widely distributed among the junipers. Ephedra foliata (23 districts), Ephedra gerardiana (20 districts) and Ephedra intermedia (19 districts) has the widest distribution range. Taxus fuana was also wider distribution range and recorded in 19 districts but its population was not very stable. These species was recorded to support local flora and fuana, especially endemics. PCORD version 5 clustered all gymnosperms species into 4 communities and all localities into 5 groups through cluster analyses. The Two Way Cluster Analyses of 66 districts (localities) resulted 4 various plant communities. The Gymnosperms in Pakistan are distributed in 3 floristic regions i.e. Western plains of the country, Northern and Western mountainous regions and Western Himalayas. The assessment of the National conservation status of these species, 10 species were found to be threatened, 6 species were endangered, 4 species were critically endangered and 1 species have become extinct (Ephedra sarcocarpa). The population of some species i.e. Taxus fuana, Ephedra gerardiana, Ephedra monosperma, Picea smithiana and Abies spectabilis is decreasing at an alarming rate.

Keywords: conservation status, gymnosperms, phytogeography, Pakistan

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Authors: Houman Tamaddon, Mehrdad Behnia, Masud Behnia

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An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray’s Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray’s Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data.

Keywords: blood flow, morphometric data, vascular tree, Strahler ordering system

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Authors: Karan R. Chavan, Srivats Gopalan, Kumudini V. Marathe

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In the current work, the comparison of degradation of malathion by single species, Pseudomonas Stutzeri, and Activated Sludge/Mixed Microbial Culture is studied in a Membrane Bioreactor. Various parameters were considered to study the effect of single species degradation compared to degradation by activated sludge. The experimental results revealed 85-90% reduction in the COD of the Malathion containing synthetic wastewater. Complete reduction of malathion was observed within 24 hours in both the cases. The critical flux was 10 LMH for both the systems. Fouling propensity, Cake and Membrane resistances were calculated thus giving an insight regarding the working of Membrane Bioreactor-based on single species and activated sludge.

Keywords: fouling, membrane bioreactor, mixed microbial culture, single species

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Authors: Meera Tandan, Mohan Timilsina, Martin Cormican, Akke Vellinga

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Background: In general practice, many infections are treated empirically without microbiological confirmation. Understanding susceptibility of antimicrobials during empirical prescribing can be helpful to reduce inappropriate prescribing. This study aims to apply a prediction model using a decision tree approach to predict the antimicrobial resistance (AMR) of urinary tract infections (UTI) based on non-clinical features of patients over 65 years. Decision tree models are a novel idea to predict the outcome of AMR at an initial stage. Method: Data was extracted from the database of the microbiological laboratory of the University Hospitals Galway on all antimicrobial susceptibility testing (AST) of urine specimens from patients over the age of 65 from January 2011 to December 2014. The primary endpoint was resistance to common antimicrobials (Nitrofurantoin, trimethoprim, ciprofloxacin, co-amoxiclav and amoxicillin) used to treat UTI. A classification and regression tree (CART) model was generated with the outcome ‘resistant infection’. The importance of each predictor (the number of previous samples, age, gender, location (nursing home, hospital, community) and causative agent) on antimicrobial resistance was estimated. Sensitivity, specificity, negative predictive (NPV) and positive predictive (PPV) values were used to evaluate the performance of the model. Seventy-five percent (75%) of the data were used as a training set and validation of the model was performed with the remaining 25% of the dataset. Results: A total of 9805 UTI patients over 65 years had their urine sample submitted for AST at least once over the four years. E.coli, Klebsiella, Proteus species were the most commonly identified pathogens among the UTI patients without catheter whereas Sertia, Staphylococcus aureus; Enterobacter was common with the catheter. The validated CART model shows slight differences in the sensitivity, specificity, PPV and NPV in between the models with and without the causative organisms. The sensitivity, specificity, PPV and NPV for the model with non-clinical predictors was between 74% and 88% depending on the antimicrobial. Conclusion: The CART models developed using non-clinical predictors have good performance when predicting antimicrobial resistance. These models predict which antimicrobial may be the most appropriate based on non-clinical factors. Other CART models, prospective data collection and validation and an increasing number of non-clinical factors will improve model performance. The presented model provides an alternative approach to decision making on antimicrobial prescribing for UTIs in older patients.

Keywords: antimicrobial resistance, urinary tract infection, prediction, decision tree

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Authors: Muhammad Riaz, Muhammad Sarwar

Abstract:

As a result of broad trapping program for the collection of fruit flies fauna of Pakistan, adults or larvae samples of fruit flies were collected from different localities. After sampling, to characterize fruit fly fauna involved, the collected samples were brought to the laboratory for their species identification. In this study, based on extensive literature records, the presence of one fruit fly species Bactrocera abbasi (Diptera: Tephritidae: Dacinae) belonging to genus Bactrocera Macquar was recognized for the first time. This new species is described and illustrated on the basis of morphological characters, supported by data on its ecology and geographic distribution. Information is also given on host plant and location of type specimen, distinguish remarks and diagnosis are as well included.

Keywords: diptera, tephritidae, bactrocera, new species, taxonomy, Pakistan

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

Procedia PDF Downloads 378