Search results for: extra trees classifier

Authors: Vibeke Sorensen, Nagaraju Thummanapalli, J. Stephen Lansing

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Inspired by the indigenous people of Borneo, Indonesia and their traditional bark cloth, artist and professor Vibeke Sorensen executed a “digital unwrapping” of several trees in Southeast Asia using a digital panorama camera and digitally “stitched” them together for printing onto sustainable silk and fashioning into the “Tree Dress”. This dress is a symbolic “un-wrapping” and “re-wrapping” of the tree’s bark onto a person as a second skin. The “digital bark” is directly responsive to the real tree through embedded and networked electronics that connect in real-time to sensors at the physical site of the living tree. LEDs and circuits inserted into the dress display the continuous measurement of the O2 / CO2, temperature, humidity, and light conditions at the tree. It is an “Internet of Living Things” (IOLT) textile that can be worn to track and interact with it. The computer system connecting the dress and the tree converts the gas emission data at the site of the real tree into sound and music as sonification. This communicates not only the scientific data but also translates it into a poetic representation. The wearer of the garment can symbolically identify with the tree, or “become one” with it by adorning its “skin.” In this way, the wearer also becomes a human agent for the tree, bringing its actual condition to direct perception of the wearer and others who may engage it. This project is an attempt to bring greater awareness to issues of deforestation by providing a direct access to living things separated by physical distance, and hopefully, to increase empathy for them by providing a way to sense individual trees and their daily existential condition through remote monitoring of data. Further extensions to this project and related issues of sustainability include the use of recycled and alternative plant materials such as bamboo and air plants, among others.

Keywords: IOLT, sonification, sustainability, tree, wearable technology

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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: Maffo Maffo Nicole Liliane, Mounmeni Kpoumie Hubert, Mbaire Matindje Karl Marx, Zapfack Louis

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Sacred forests play a valuable role in conserving local biodiversity and provide numerous ecosystem services in Cameroon. The study was carried out in the sacred forests of Bandrefam and Batoufam (western Cameroon). The aim was to estimate the diversity of woody species, carbon stocks and degradation factors in these sacred forests. The floristic inventory was carried out in plots measuring 25m × 25m for trees with diameters greater than 10 cm and 5m × 5m for trees with diameters less than 10 cm. Carbon stocks were estimated using the non-destructive method and the allometric equations. Data on degradation factors were collected using semi-structured surveys in the Bandrefam and Batoufam neighborhoods. The floristic inventory identified 65 species divided into 57 genera and 30 families in the Bandrefam Sacred Forest and 45 species divided into 42 genera and 27 families in the Batoufam Sacres Forest. The families common to both sacred forests are as follows: Phyllanthaceae, Fabaceae, Moraceae, Lamiaceae, Malvaceae, Rubiaceae, Meliaceae, Anacardiaceae, and Sapindaceae. Three genera are present in both sites. These are: Albizia, Macaranga, Trichillia. In addition, there are 27 species in common between the two sites. The total carbon stock is 469.26 tC/ha at Batoufam and 291.41 tC/ha at Bandrefam. The economic value varies between 15 823 877.05 fcfa at Batoufam and 9 825 530.528 fcfa at Bandrefam. The study shows that despite the sacred nature of these forests, they are subject to degradation factors such as bushfires (35.42 %), the creation of plantations (23.96 %), illegal timber exploitation (21.88 %), young people's lack of interest in the notion of conservation (9.38 %), climate change (7.29 %) and growing urbanization (2.08 %). These factors threaten biodiversity and reduce carbon storage in these forests.

Keywords: sacred forests, degradation factors, carbon stocks, semi-structured surveys

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Authors: Bhalke D. G., Bormane D. S., Kharate G. K.

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This paper presents classification of musical instrument using machine learning techniques. The classification has been carried out using temporal, spectral, cepstral and wavelet features. Detail feature analysis is carried out using separate and combined features. Further, instrument model has been developed using K-Nearest Neighbor and Support Vector Machine (SVM). Benchmarked McGill university database has been used to test the performance of the system. Experimental result shows that SVM performs better as compared to KNN classifier.

Keywords: feature extraction, SVM, KNN, musical instruments

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Authors: M. N. Kadir, M. M. H. Oliver, T. Naher

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The study assesses the areal extent of riverine flood in the flood-prone area of Faridpur District of Bangladesh using hydrological model and Geographic Information System (GIS). In the context of preparing the inundation map, flood frequency analysis was carried out to assess flooding for different flood magnitudes. Flood inundation maps were prepared based on DEM, and discharge at the river using Delft-3D model. LANDSAT satellite images have been used to develop a land cover map in the study area. The land cover map was used for mapping of cropland area. By incorporating the inundation maps on the land cover map, agricultural damage was assessed. Present monetary values of crop damage were collected through field survey from actual flood of the study area. Two different inundation maps were produced from the model for the year 2000 and 2016. In the year 2000, the floods began in the month of July, whereas in the case of the year 2016 is started in August. Under both cases, most of the areas were found to have been flooded in the month of September followed by flood recession. In order to prepare the land cover maps, four categories of LCs were considered viz., cropland, water body, trees, and rivers. Among the 755791 acres area of Faridpur District, the croplands were categorized to be 334,589 acres, followed by water bodies (279900 acres), trees (101930 acres) and rivers 39372 (acres). Damage assessment data revealed that 40% of the total cropland area had been affected by the flood in the year 2000, whereas only 19% area was affected by the 2016 flood. The study concluded that September is the critical month for cropland protection since the highest flood is expected at this time of the year in Faridpur. The northwestern and the southwestern part of the district was categorized as most vulnerable to flooding.

Keywords: agricultural damage, Delft-3d, flood management, land cover map

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Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

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Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Seyed Mehdi Ghezi, Hesam Hasanpoor

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This scientific article explores enhancement methods for ensemble learning with the aim of improving the performance of classifiers in the analysis and classification of brain signals. The research approach in this field consists of two main parts, each with its own strengths and weaknesses. The choice of approach depends on the specific research question and available resources. By combining these approaches and leveraging their respective strengths, researchers can enhance the accuracy and reliability of classification results, consequently advancing our understanding of the brain and its functions. The first approach focuses on utilizing machine learning methods to identify the best features among the vast array of features present in brain signals. The selection of features varies depending on the research objective, and different techniques have been employed for this purpose. For instance, the genetic algorithm has been used in some studies to identify the best features, while optimization methods have been utilized in others to identify the most influential features. Additionally, machine learning techniques have been applied to determine the influential electrodes in classification. Ensemble learning plays a crucial role in identifying the best features that contribute to learning, thereby improving the overall results. The second approach concentrates on designing and implementing methods for selecting the best classifier or utilizing meta-classifiers to enhance the final results in ensemble learning. In a different section of the research, a single classifier is used instead of multiple classifiers, employing different sets of features to improve the results. The article provides an in-depth examination of each technique, highlighting their advantages and limitations. By integrating these techniques, researchers can enhance the performance of classifiers in the analysis and classification of brain signals. This advancement in ensemble learning methodologies contributes to a better understanding of the brain and its functions, ultimately leading to improved accuracy and reliability in brain signal analysis and classification.

Keywords: ensemble learning, brain signals, classification, feature selection, machine learning, genetic algorithm, optimization methods, influential features, influential electrodes, meta-classifiers

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Authors: Maher J. Tadros

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This research was conducted to study the effect of different salinity concentrations on the plant water relation and forage quality on two multipurpose forest trees species seedlings Leucaena leucocephala (Lam.) de wit and Acacia saligna (Labill.). Five different salinity concentrations mixture between sodium chloride and calcium chloride (v/v, 1:1) were applied. The control (Distilled Water), 2000, 4000, 6000, and 8000 ppm were used to water the seedlings for 3 months. The research results presented showed a marked variation among the two species in response to salinity. The Leucaena was able to withstand the highest level of salinity compared to Acacia all over the studied parameters except in the relative water content. Although all the morphological characteristics studied for the two species showed a marked decrease under the different salinity concentrations, except the shoot/root ratio that showed a trend of increase. The water stress measure the leaf water potential was more negative with as the relative water content increase under that saline conditions compared to the control. The forage quality represented by the crude protein and nitrogen content were low at 6000 ppm compared to the 8000 ppm in L. Leucocephala that increased compared that level in A. saligna. Also the results showed that growing both Leucaena and Acacia provide a good source of forage when that grow under saline condition which will be of great benefits to the agricultural sector especially in the arid and semiarid areas were these species can provide forage with high quality forage all year around when grown under irrigation with saline. This research recommended such species to be utilized and grown for forages under saline conditions.

Keywords: plant water relations, growth performance, salinity stress, protein content, forage quality, multipurpose trees

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Authors: Stanis Koko Nyalongomo, Benjamin Mputela Bankanza, Moise Kisempa Mahungudi

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Several areas in the Democratic Republic of Congo (DRC) experience serious problems of streaming and soil erosion. Erosion leads to degradation of soil health, and the three main causative factors of similar importance are deforestation, overgrazing, and land agricultural mismanagement. Degradation of soil health leads to a decrease in agricultural productivity and carbon dioxide (CO₂), and other greenhouse gas emissions. Agricultural productivity low, and sanitation-related diseases are a concern of a majority of DRC rural people -whose main livelihoods are conventional smallholder agriculture- due to degradation of agricultural soil health and prevalence of inappropriate sanitation in rural areas. Land management practices that increase soil carbon stocks on agricultural lands with practices including conservation agriculture and agroforestry do not only limit CO₂ emissions but also help prevent erosion while enhancing soil health and productivity. Promotion to adopt sustainable land management practices, especially conversion to well-managed agroforestry practices, is a necessity. This needs to be accompanied by incentives. Methods that incite smallholders to adopt practices that increase carbon stocks in agricultural lands and enhance soil health and productivity for social, economic, and environmental benefits, and give them the ability to get and use household dry toilets -included activities to inform and raise smallholder households awareness on the conversion of croplands to well-managed agroforestry systems through planting at least 20 fruit trees and/or acacias, soil carbon and practices that sequester it in soil and ecological sanitation; and offer smallholders technique and material supports and incentives under the form of dry toilets constructed for free for well-managed agroforestry implementation- were carried out to address problems of soil erosion as well as agricultural productivity and sanitation-related diseases. In 2018 and 2019, 19 of 23 targeted smallholder households expressed their satisfaction and converted their croplands to agroforestry through planting 374 trees, and each gotten 1 dry toilet constructed for free. Their neighbors expressed a willingness to participate in the project. Conversion to well-managed agroforestry practices offers many advantages to both farmers and the environment. The strategy of offering smallholders incentives for soil-friendly agricultural practices, especially well-managed agroforestry, is one of the solutions to prevent soil erosion. DRC rural people whose majority are smallholder households, need to be able to get and use dry toilets. So, dry toilets could be offered like incentives for well-managed agroforestry practices. Given the many advantages agroforestry and dry toilet can offer, recommendations are made for funding organizations to support such projects that promote the adoption of soil health practices.

Keywords: agroforestry, croplands, soil carbon, soil health

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Authors: Huan-Chieh Chiu, Hung-Shuo Wu, Chien-Hao Wang, Yu-Cheng Yang, Ching-Ya Tseng, Joe-Air Jiang

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Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.

Keywords: damage level monitoring, drift ratio, fragility curve, smart grid, transmission tower

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Authors: Esmaeil Kouhgardi, Elaheh Shakerdargah

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The mangrove ecosystem is a complex of various inter-related elements in the land-sea interface zone which is linked with other natural systems of the coastal region such as corals, sea-grass, coastal fisheries and beach vegetation. The mangrove ecosystem consists of water, muddy soil, trees, shrubs, and their associated flora, fauna and microbes. It is a very productive ecosystem sustaining various forms of life. Its waters are nursery grounds for fish, crustacean, and mollusk and also provide habitat for a wide range of aquatic life, while the land supports a rich and diverse flora and fauna, but pollutions may affect these characteristics. Iran has the lowest share of Persian Gulf pollution among the eight littoral states; environmental experts are still deeply concerned about the serious consequences of the pollution in the oil-rich gulf. Prolongation of critical conditions in the Persian Gulf has endangered its aquatic ecosystem. Water purification equipment, refineries, wastewater emitted by onshore installations, especially petrochemical plans, urban sewage, population density and extensive oil operations of Arab states are factors contaminating the Persian Gulf waters. Population density has been the major cause of pollution and environmental degradation in the Persian Gulf. Persian Gulf is a closed marine environment which is connected to open waterways only from one way. It usually takes between three and four years for the gulf's water to be completely replaced. Therefore, any pollution entering the water will remain there for a relatively long time. Presently, the high temperature and excessive salt level in the water have exposed the marine creatures to extra threats, which mean they have to survive very tough conditions. The natural environment of the Persian Gulf is very rich with good fish grounds, extensive coral reefs and pearl oysters in abundance, but has become increasingly under pressure due to the heavy industrialization and in particular the repeated major oil spillages associated with the various recent wars fought in the region. Pollution may cause the mortality of mangrove forests by effect on root, leaf and soil of the area. Study was showed the high correlation between industrial pollution and mangrove forests health in south of Iran and increase of population, coupled with economic growth, inevitably caused the use of mangrove lands for various purposes such as construction of roads, ports and harbors, industries and urbanization.

Keywords: Mangrove forest, pollution, Persian Gulf, population, environment

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Authors: Oluwatobi Emmanuel Olaniyi, Babafemi George Ogunjemite

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The high rate of infrastructural development in Ikogosi warm spring towards harnessing her great ecotourism potentials calls for a serious concern, as more forest areas are been opened up for public access and the landscape is modified. On this note, we investigated the implication of ecotourism development on the floristic composition and forest structure in Ikogosi. The study aimed at identifying the past and present status of infrastructural development, assessing and comparing the floristic composition and structure of the built- up/ recreational areas and undisturbed forested areas, to infer on the impact of ecotourism development on the study site. We conducted stakeholder interview and field observation to identify the past and present status of infrastructural development respectively. A total of ten quadrants were employed in the vegetation assessment to characterize the woody tree species composition, diameter at breast height and height, to obtain mean indices characterizing each part of the site. These indices were compared using T – test analysis. A total of 49 different woody tree species distributed in 21 families were identified in the built-in/ recreational areas while 67 different woody tree species belonging to 25 families were recorded in the undeveloped forested areas. Although, the latter has a higher mean diameter at breast height of woody trees, it was not significantly different from the former (T-test = -0.74, p = 0.46). On the contrary, the built-up area had a higher mean trees height than the undeveloped areas, but the difference was not statistically significant (T-test= 1.04, p = 0.30). Despite these, the slight reduction in richness and diversity of the woody tree species in the built- up/ recreational areas implies mitigating the negative effects of infrastructural development on the warm spring's vegetation.

Keywords: ecosystem services, forest structure, vegetation assessment, warm-spring

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Authors: Makhosi Buthelezi

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Mitochondrial DNA cytochrome c oxidase I (COI) gene analyses linked the South African groundnut leaf miner (GLM) to the Australian soya bean moth Aproaerema simplexella (Walker) and Indian Aproaerema modicella (Deventer). Thus, the genetic relatedness of GLM, A. simplexela, and A. modicella was examined by performing mitochondrial and nuclear (COI, cytochrome oxidase subunit II (COII), mitochondrial cytochrome b (CYTB), nuclear ribosomal 28S (28S) and intergenic spacer elongation factor-1 alpha ( EF-1 ALPHA) on 44 specimens collected from South Africa, four from Mozambique, and three each from single locations in India and Australia. Phylogenetic analyses were conducted using the Maximum Parsimony (MP) and Neighbour-Joining (NJ) methods. All of the datasets of the five DNA gene regions that were sequenced were also analyzed using the Basic Local Alignment Search Tool (BLAST) to find the closest matches for inclusion in the phylogenetic trees as outgroups and for purposes of information. In the phylogenetic trees for COI, COII, cytb and EF-1 ALPHA, a similar pattern was observed in the way that the sequences assembled into different groups; i.e., some sequences of A. simplexella from Australia were grouped separately from the others, but some Australian sequences grouped with those of the GLM from South Africa, India, and Mozambique. In the phylogenetic tree for 28S, all sequences from South Africa, Australia, India, and Mozambique grouped together and formed one group. For COI, genetic pairwise distance ranged from 0.97 to 3.60 %, for COII it ranged from 0.19% to 2.32%, for cytb it ranged from 0.25 to 9.77% and for EF-1 ALPHA it ranged 0.48 to 6.99%. Results of this study indicate that these populations are genetically related and presumably constitute a single species. Thus, further molecular and morphological studies need to be undertaken in order to resolve this apparent conundrum on the taxonomy of these populations.

Keywords: aproaerema modicella, aproaerema simplexella, mitochondrial DNA, nuclear DNA

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Authors: Jim Shih-Chiao Chin , Tsai Lin Hsu, Shui Lien Chen

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This article extends the relation between company’s employee and customers in market. According to the previous researches, most researchers analyzed and focused on customers’ brand perception. In the recently, some scholars star to explore the brand management from company viewpoint. The aim of this study is to explore whether consumers perception would be affected by the firm brand. This research would like to examine the relationship between individual consumers and corporate brands in the business-to-consumers sector. First, the study develops a framework that the connection with consumer and company. Second, this article uses three dimensions, brand knowledge, brand commitment, and brand equity to measure employees’ loyalty of brand and applies brand relationship quality to gauge the level of brand’s importance in consumer’s mind. This paper uses SPSS 20.0 and AMOS 20.0 to test consumers’ minds toward the brand equity which the company provides. There are totally 862 valid questionnaires returned, and 431 participants are consumers; the other 431 participants are employees. Those questionnaires are one-by-one to consumer and employee so those are 431 pairs questionnaires. Based on 431 pairs of consumers and company’s employees, analyzed results show that brand knowledge and brand commitment play important roles influencing brand equity. The results also demonstrate the extra-role brand equity positively impact on the brand relationship quality of consumers. In addition, the findings reveal that the company can improve brand relationship quality of consumers by enhancing extra-role brand equity. There is a sufficient evidence denote that brand relationship quality not only shows about the brand of customers’ thought but also implies company how to build the brand to impress on consumers. These findings provide the degree of the brand in consumers’ cognition. The brand-owner employee can reference the conclusion to creative new strategic to the next time or can be one of the company’s competitive advantages. Those results and conclusions are contributed to management practice and future.

Keywords: brand knowledge, brand commitment, brand equity, brand relationship quality

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Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

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Authors: Petr Daniel Kovarik, Matt Kennedy, James Adams, Ajay Wilson, Andy Burns, Charles Kelly, Malcolm Jackson, Rahul Patil, Shahid Iqbal

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Introduction: Osteoradionecrosis (ORN) is a recognised toxicity of radiotherapy (RT) for head and neck cancer (HNC). Existing literature lacks any generally accepted definition and staging system for this toxicity. Objective: The objective is to analyse the outcome of the surgical and nonsurgical treatments of ORN. Material and Method: Data on 2303 patients treated for HNC with radical or adjuvant RT or RT-chemotherapy from January 2010 - December 2021 were retrospectively analysed. Median follow-up to the whole group of patients was 37 months (range 0–148 months). Results: ORN developed in 185 patients (8.1%). The location of ORN was as follows; mandible=170, maxilla=10, and extra oral cavity=5. Multiple ORNs developed in 7 patients. 5 patients with extra oral cavity ORN were excluded from treatment analysis as the management is different. In 180 patients with oral cavity ORN, median follow-up was 59 months (range 5–148 months). ORN healed in 106 patients, treatment failed in 74 patients (improving=10, stable=43, and deteriorating=21). Median healing time was 14 months (range 3-86 months). Notani staging is available in 158 patients with jaw ORN with no previous surgery to the mandible (Notani class I=56, Notani class II=27, and Notani class III=76). 28 ORN (mandible=27, maxilla=1; Notani class I=23, Notani II=3, Notani III=1) healed spontaneously with a median healing time 7 months (range 3–46 months). In 20 patients, ORN developed after dental extraction, in 1 patient in the neomandible after radical surgery as a part of the primary treatment. In 7 patients, ORN developed and spontaneously healed in irradiated bone with no previous surgical/dental intervention. Radical resection of the ORN (segmentectomy, hemi-mandibulectomy with fibula flap) was performed in 43 patients (all mandible; Notani II=1, Notani III=39, Notani class was not established in 3 patients as ORN developed in the neomandible). 27 patients healed (63%); 15 patients failed (improving=2, stable=5, deteriorating=8). The median time from resection to healing was 6 months (range 2–30 months). 109 patients (mandible=100, maxilla=9; Notani I=3, Notani II=23, Notani III=35, Notani class was not established in 9 patients as ORN developed in the maxilla/neomandible) were treated conservatively using a combination of debridement, antibiotics and Pentoclo. 50 patients healed (46%) with a median healing time 14 months (range 3–70 months), 59 patients are recorded with persistent ORN (improving=8, stable=38, deteriorating=13). Out of 109 patients treated conservatively, 13 patients were treated with Pentoclo only (all mandible; Notani I=6, Notani II=3, Notani III=3, 1 patient with neomandible). In total, 8 patients healed (61.5%), treatment failed in 5 patients (stable=4, deteriorating=1). Median healing time was 14 months (range 4–24 months). Extra orally (n=5), 3 cases of ORN were in the auditory canal and 2 in mastoid. ORN healed in one patient (auditory canal after 32 months. Treatment failed in 4 patients (improving=3, stable=1). Conclusion: The outcome of the treatment of ORN remains in general, poor. Every effort should therefore be made to minimise the risk of development of this devastating toxicity.

Keywords: head and neck cancer, radiotherapy, osteoradionecrosis, treatment outcome

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Authors: Debit Datta, Jeffrey J. Coleman, Scott A. Enebak, Lori G. Eckhardt

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Loblolly pine (Pinus taeda) is a leading productive timber species in the southeastern USA. Over the past three years, an emerging threat is expressed by successive needle defoliation followed by stunted growth and tree mortality in loblolly pine plantations. Considering economic significance, it has now become a rising concern among landowners, forest managers, and forest health state cooperators. However, the symptoms of the disease were perplexed somewhat with root disease(s) and recurrently attributed to invasive Phytophthora species due to the similarity of disease nature and devastation. Therefore, the study investigated the potential causal agent of this disease and characterized the fungi associated with loblolly pine needle defoliation in the southeastern USA. Besides, 70 trees were selected at seven long-term monitoring plots at Chatom, Alabama, to monitor and record the annual disease incidence and severity. Based on colony morphology and ITS-rDNA sequence data, a total of 28 species of fungi representing 17 families have been recovered from diseased loblolly pine needles. The native brown-spot pathogen, Lecanosticta acicola, was the species most frequently recovered from unhealthy loblolly pine needles in combination with some other common needle cast and rust pathogen(s). Identification was confirmed using morphological similarity and amplification of translation elongation factor 1-alpha gene region of interest. Tagged trees were consistently found chlorotic and defoliated from 2019 to 2020. The current emergence of the brown-spot pathogen causing loblolly pine mortality necessitates the investigation of the role of changing climatic conditions, which might be associated with increased pathogen pressure to loblolly pines in the southeastern USA.

Keywords: brown-spot needle blight, loblolly pine, needle defoliation, plantation forestry

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Authors: O.F. Akinmoladun, F.N. Fon, C.T. Mpendulo, O. Okoh

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The sustainability of livestock production is under threat as a result of water scarcity, fluctuating precipitation, and high environmental temperature. These combined stressors have impacted negatively on general animal production and welfare, necessitating a very reliable and cost-effective management practices, especially in arid and water-limited regions of the world. Instead of the above, this study was designed to investigate the growth performance and physiological response of water-restricted Xhosa ear-lobe goats fed diets supplemented with single or multiple vitamin C (VC) during summer. The total forty-eight goats used for the experiment were balanced for body weight and randomly assigned to the seven treatment groups (seven goats/treatment): GI (W100%); GII (W70%); GIII (W50%); GIV (W70%+3g/day VC); GV ((W50% +3g/day VC); GVI (W70%+3g/d VC+extra 5g on every eight-day); GVII (W50%+3g/d VC+extra 5g on every eight-day). The design was a complete randomized design and VC was administered per os. At the end of the 75-day feeding trial, GIII (W50%) animals were the most affected (P<0.05) and the effect was more pronounced in their body condition scores (BCs). Weight loss and depression in feed intake due to water restriction (P<0.05) were attenuated by VC treated groups (GIV-GVII). Changes in body thermal gradient (BTG) and rectal temperature (RcT) were similar (P>0.05) across the various experimental groups. The attenuation effect of VC was significant in responses to respiratory rate (RR) and cortisol. Supplementation of VC (either single or multiple) did not significantly (P>0.05) improve water restriction effect on body condition scores (BCs) and FAMACHA©. The current study found out that Xhosa ear lobe goats can adapt to the prevailing bioclimatic changes and limited water intake. However, supplementation of vitamin C can be beneficial at modulating these stressful stimuli. Continuous consistencies in the outcome of vitamin C on water-stressed animals can help validate recommendations especially to farmers in the arid and water-limited regions across the globe.

Keywords: vitamin C, Xhosa ear-lobe, thermotolerance, water stress

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Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: Mohammadreza Hajialigol, Nargues Falahi Charkhabi, Fatemeh Shahryari, Saadat Sarikhani

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BACKGROUND AND OBJECTIVES Iran is the third producer of Persian walnut worldwide. However, its walnut trees have been under threat from decline during last decade. Walnut canker caused by B. nigrifluens and B. rubrifaciens was recorded in multiple regions of Iran. Furthermore, Brenneria rosae subsp. rosae and Gibbsiella quercinecans were recently recognized as responsible for walnut decline in northwestern Iran. This study aimed to identify the causal agent of walnut decline in Kermanshah and Isfahan. MATERIAL AND METHODS Symptomatic samples were collected from affected walnut trees of Kermanshah and Isfahan provinces. The pathogenicity of strains was proved on immature walnut fruits cv. ‘Hartley’ and young green twigs of two-year-old walnut seedling cv. ‘Chandler’. Pathogenic strains were subjected to conventional phenotypic tests. 16S rRNA, gyrB, and infB genes were partially amplified and sequenced. RESULTS Irregular longitudinal cankers and dark lesions were observed in the outer and inner bark, respectively. Twenty-four strains were isolated on EMB-agar media. Fourteen strains were able to cause necrosis and a dark-colored region in the mesocarp and on young green twigs around the inoculation site 14 and 30 days post-inoculation, respectively. Strains were able to hydrolyze Tween 20, Tween 80, gelatin and esculin, however, did not produce indole or urease. Pairwise comparison, the 16S rRNA gene nucleotide sequences of strain I2 were 100% identical with those of Rahnella victoriana FRB 225T. Moreover, a phylogenetic tree reconstructed based on the concatenated sequences of two housekeeping gene fragments, gyrB (601 bp) and infB (615 bp), revealed that the strains I2, I5, and KE6 were clustered with R. victoriana FRB 225T. CONCLUSION To the best of our knowledge, this is the first report of R. victoriana in association with walnut decline. This result is necessary to find resistant genotypes.

Keywords: emerging pathogens, Iran, juglans regia, MLSA

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Authors: Abeer N. Alshukairi, Abdulrahman A. Alrajhi, Abdulfattah W. Alamri, Adel F. Alothman

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We described the nosocomial transmission of a pre-XDR or an MDR case of pulmonary tuberculosis in a HIV negative health care worker in an area endemic for MDR & XDR tuberculosis. With inadequate therapy and non-compliance, his strain developed acquired resistance and he presented with extra-pulmonary XDR tuberculosis in the form of multi-focal osteomyelitis and encysted pleural effusion. He was cured after 2 years of therapy with various anti-tuberculous drugs in addition to interferon gamma.

Keywords: osteomyelitis, treatment, XDR tuberculosis, successful treatment

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Authors: Jyoti Bharti, Navneet Manjhi, M. K.Gupta, Bimi Jain

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A reliable gait features are required to extract the gait sequences from an images. In this paper suggested a simple method for gait identification which is based on moments. Moment values are extracted on different number of frames of gray scale and silhouette images of CASIA database. These moment values are considered as feature values. Fuzzy logic and nearest neighbour classifier are used for classification. Both achieved higher recognition.

Keywords: gait, fuzzy logic, nearest neighbour, recognition rate, moments

Procedia PDF Downloads 723

Authors: Wiwin Tyas Istikowati, Futoshi Ishiguri, Haruna Aisho, Budi Sutiya, Imam Wahyudi, Kazuya Iizuka, Shinso Yokota

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The objective of this study was to investigate the anatomical characteristics of three native fast-growing species, terap (Artocarpus elasticus Reinw. ex Blume), medang (Neolitsea latifolia (Blume) S. Moore), and balik angin (Alphitonia excelsa (Fenzel) Reissek ex Benth) growing in the secondary forest in South Kalimantan, Indonesia for evaluating the possibility of tree breeding for wood quality. Cell lengths were investigated for 5 trees in each species at several different height positions (1.0, 3.0, 5.0, 7.0, 9.0, and 11.0 m above the ground). The mean values of fiber and vessel element lengths in terap, medang, and balik angin were 1.52 and 0.44, 1.16 and 0.53, and 1.02 and 0.49 mm, respectively. Fiber length in terap and balik angin gradually increased from pith to bark, whereas it increased up to 2 cm and then became nearly constant to the bark in medang. Vessel element length was almost constant from pith to bark in terap and balik angin, while slightly increased from pith to bark in medang. Fiber length in terap has a fluctuation pattern from ground level to top of the tree. It decreased up to 3 m above the ground, increased up to 5 m, and then decreased to the top of the tree. On the other hand, vessel element length slightly increased up to 5 m above the ground, and then decreased to the top of the tree. Both fiber and vessel element lengths in medang were almost constant from ground level to top of the tree, whereas decreased from ground level to top of the tree in balik angin. Significant difference at 1% level among trees was found in both fiber and vessel element length in both radial and longitudinal directions for terap and medang. Based on obtained results, it is concluded that the wood quality in fiber and vessel element lengths of terap and medang can be improved by tree breeding programs.

Keywords: anatomical properties, fiber length, vessel elements length, fast-growing species

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: Talaat Ahmed, Amna Babssail

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Mangroves are evergreen trees and grow along the coastal areas of Qatar. The largest and oldest area of mangroves can be found around Al-Thakhira and Al-Khor. Other mangrove areas originate from fairly recent plantings by the government, although unfortunately the picturesque mangrove lake in Al-Wakra has now been uprooted. Avicinnia marina is the predominant mangrove species found in the region. Mangroves protect and stabilize low lying coastal land, and provide protection and food sources for estuarine and coastal fishery food chains. They also serve as feeding, breeding and nursery grounds for a variety of fish, crustaceans, reptiles, birds and other wildlife. A total of 21 individuals of A. marina, representing seven diverse Natural and artificial populations, were sampled throughout its range in Qatar. Leaves from 2-3 randomly selected trees at each location were collected. The locations are as follows: Al-Rawis, Ras-Madpak, Fuwairt, Summaseima, Al-khour, AL-Mafjar and Zekreet. Total genomic DNA was extracted using commercial DNeasy Plant System (Qiagen, Inc., Valencia, CA) kit to be used for genetic diversity analysis. Total of 12 (Inter-Simple Sequence Repeat) ISSR primers were used to amplify DNA fragments using genomic DNA. The 12 ISSR primers amplified polymorphic bands among mangrove samples in different areas as well as within each area indicating the existing of variation within each area and among the different areas of mangrove in Qatar. The results could characterize Avicinnia marina populations exist in different areas of Qatar and establish DNA fingerprint documentations for mangrove population to be used in further studies. Moreover, existing of genetic variation within and among Avicinnia marina populations is a strong indication for the ability of such populations to adapt different environmental conditions in Qatar. This study could be a warning to save mangrove in Qatar and save the environment as well.

Keywords: DNA fingerprint, Avicinnia marina, genetic analysis, Qatar

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Authors: Jubee Varghese, Pouria Hafiz

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Increased use of lightweight concrete in the construction industry is mainly due to its reduction in the weight of the structural elements, which in turn reduces the cost of production, transportation, and the overall project cost. However, the structural application of these lightweight concrete structures is limited due to its reduced density. Hence, further investigations are in progress to study the effect of fiber inclusion in improving the mechanical properties of lightweight concrete. Incorporating structural steel fibers, in general, enhances the performance of concrete and increases its durability by minimizing its potential to cracking and providing crack arresting mechanism. In this research, Geometric and Materially Non-linear Analysis (GMNA) was conducted for Finite Element Modelling using a software known as ABAQUS, to investigate the structural behavior of lightweight concrete with and without the addition of steel fibers and shear reinforcement. 21 finite element models of beams were created to study the effect of steel fibers based on three main parameters; fiber volume fraction (Vf = 0, 0.5 and 0.75%), shear span to depth ratio (a/d of 2, 3 and 4) and ratio of area of shear stirrups to spacing (As/s of 0.7, 1 and 1.6). The models created were validated with the previous experiment conducted by H.K. Kang et al. in 2011. It was seen that the lightweight fiber reinforcement can replace the use of fiber reinforced normal weight concrete as structural elements. The effect of an increase in steel fiber volume fraction is dominant for beams with higher shear span to depth ratio than for lower ratios. The effect of stirrups in the presence of fibers was very negligible; however; it provided extra confinement to the cracks by reducing the crack propagation and extra shear resistance than when compared to beams with no stirrups.

Keywords: ABAQUS, beams, fiber-reinforced concrete, finite element, light weight, shear span-depth ratio, steel fibers, steel-fiber volume fraction

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Authors: Snezana Rajkovic, Miroslava Markovic, Ljubinko Rakonjac, Aleksandar Lucic, Radoslav Rajkovic

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Woolly apple aphid, Eriosoma lanigerum (Hausmann) is a widely distributed pest of apple trees, especially where its parasites have been killed by insecticides. It can also be found on pear, hawthorn, mountain ash, and elm trees. Relatively small to medium-sized aphids, characterized by a reddish-brown body, a blood-red stain when crushed and a fluffy, flocculent wax covering. Specialized dermal glands produce the characteristic fluffy or powdery wax, which gives E. lanigerum its characteristic 'woolly' appearance. Also, woolly apple aphid is a problemm in nursery production of spure.The experiments were carried out in the nursery “Nevade” in Gornji Milanovac, "Srbijasume" on the spruce seedlings, aged 2 years. In this study, organic insecticide King Bo, aqueous solution (a. i. oxymatrine 0.2% + psoralen 0.4%), manufacturer Beijing Kingbo Biotech Co. Ltd., Beijing, China. extracted from plants and used as pesticides in nursery production were investigated. King Bo, bioinsecticide is manufactured from refined natural herbal extract several wild medicinal plants, such as Sophora flavescens Ait, Veratrum nigrum L, A. Carmichael, etc. Oxymatrine 2.4 SL is a stomach poison that has antifeeding and repellent action. This substance stimulates development and growth in a host plant and also controls the appearance of downy mildew.The trials were set according to instructions of methods-monitoring of changes in the number of larvae and adults compared to before treatment. The treatment plan was made according to fully randomized block design. The experiment was conducted in four repetitions. The basic plot had the area of 25 m2. Phytotoxicity was estimated by PP methods 1/135 (2), the intensity of infection according to Towsend-Heuberger, the efficiency by Abbott, the analysis of variance with Ducan test and PP/181 (2).

Keywords: bioinsecticide, efficacy, nurssery production, woolly apple aphid

Procedia PDF Downloads 502

Authors: Pantana Tor-Ngern

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In the global water cycle, tree water use (Tr) largely contributes to evapotranspiration which is the total amount of water evaporated from terrestrial ecosystems to the atmosphere, regulating climates. Tree water use responds to environmental factors, including atmospheric humidity and sunlight (represented by vapor pressure deficit or VPD and photosynthetically active radiation or PAR, respectively) and soil moisture. In forests, Tr responses to such factors depend on species and their spatial and temporal variations. Tropical forests in Southeast Asia (SEA) have experienced land-use conversion from abandoned agricultural practices, resulting in patches of forests at different stages including old-growth and secondary forests. Because the inherent structures, such as canopy height and tree density, significantly vary among forests at different stages and can strongly affect their respective microclimate, Tr and its responses to changing environmental conditions in successional forests may differ. Daily and seasonal variations in the environmental factors may exert significant impacts on the respective Tr patterns. Extrapolating Tr data from short periods of days to longer periods of seasons or years can be complex and is important for estimating long-term ecosystem water use which often includes normal and abnormal climatic conditions. Thus, this study aims to investigate the diurnal variation of Tr, using measured sap flux density (JS) data, with changes in VPD in eight evergreen tree species in an old-growth forest (hereafter OF; >200 years old) and a young forest (hereafter YF, <10 years old) in Khao Yai National Park, Thailand. The studied species included Sysygium syzygoides, Aquilaria crassna, Cinnamomum subavenium, Nephelium melliferum, Altingia excelsa in OF, and Syzygium nervosum and Adinandra integerrima in YF. Only Sysygium antisepticum was found in both forest stages. Specifically, hysteresis, which indicates the asymmetrical changes of JS in response to changing VPD across daily timescale, was examined in these species. Results showed no hysteresis in all species in OF, except Altingia excelsa which exhibited a 3-hour delayed JS response to VPD. In contrast, JS of all species in YF displayed one-hour delayed responses to VPD. The OF species that showed no hysteresis indicated their well-coupling of their canopies with the atmosphere, facilitating the gas exchange which is essential for tree growth. The delayed responses in Altingia excelsa in OF and all species in YF were associated with higher JS in the morning than that in the afternoon. This implies that these species were sensitive to drying air, closing stomata relatively rapidly compared to the decreasing atmospheric humidity (VPD). Such behavior is often observed in trees growing in dry environments. This study suggests that detailed investigation of JS at sub-daily timescales is imperative for better understanding of mechanistic responses of trees to the changing climate, which will benefit the improvement of earth system models.

Keywords: sap flow, tropical forest, forest succession, thermal dissipcation probe

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Authors: Ali S. Gargoum

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Graphical modeling plays an important role in providing efficient probability calculations in high dimensional problems (computational efficiency). In this paper, we address one of such problems where we discuss fragmenting puff models and some distributional assumptions concerning models for the instantaneous, emission readings and for the fragmenting process. A graphical representation in terms of a junction tree of the conditional probability breakdown of puffs and puff fragments is proposed.

Keywords: graphical models, influence diagrams, junction trees, Bayesian nets

Procedia PDF Downloads 374