Search results for: vascular tree

Authors: Sammy Kibor, Filip Huyghe, Marc Kochzius, James Kairo

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Goldstripe Sardinella, Sardinella gibbosa, (Bleeker, 1849) is a commercially and ecologically important small pelagic fish common in the Western Indian Ocean region. The present study aimed to assess genetic diversity and population structure of the species in the Kenya-Tanzania transboundary area using mtDNA and msDNA markers. Some 630 bp sequence in the mitochondrial DNA (mtDNA) Cytochrome C Oxidase I (COI) and five polymorphic microsatellite DNA loci were analyzed. Fin clips of 309 individuals from eight locations within the transboundary area were collected between July and December 2018. The S. gibbosa individuals from the different locations were distinguishable from one another based on the mtDNA variation, as demonstrated with a neighbor-joining tree and minimum spanning network analysis. None of the identified 22 haplotypes were shared between Kenya and Tanzania. Gene diversity per locus was relatively high (0.271-0.751), highest Fis was 0.391. The structure analysis, discriminant analysis of Principal component (DAPC) and the pair-wise (FST = 0.136 P < 0.001) values after Bonferroni correction using five microsatellite loci provided clear inference on genetic differentiation and thus evidence of population structure of S. gibbosa along the Kenya-Tanzania coast. This study shows a high level of genetic diversity and the presence of population structure (Φst =0.078 P < 0.001) resulting to the existence of four populations giving a clear indication of minimum gene flow among the population. This information has application in the designing of marine protected areas, an important tool for marine conservation.

Keywords: marine connectivity, microsatellites, population genetics, transboundary

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Authors: J. Dharmaraj, C. Gunasekaran

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Invertebrates are the reliable ecological indicators of disturbance of the forest ecosystems and they respond to environment changes more quickly than other fauna. Among these the terrestrial invertebrates are vital to functioning ecosystems, contributing to processes such as decomposition, nutrient cycling and soil fertility. The natural ecosystems of the forests have been subject to various types of disturbances, which lead to decline of flora and fauna. The comparative diversity of micro-arthropods in natural forest, wattle plantation and eucalyptus plantations were studied in Nilgiris. The study area was divided in to five major sites (Emerald (Site-I), Thalaikundha (Site-II), Kodapmund (Site-III), Aravankad (Site-IV), Kattabettu (Site-V). The research was conducted during period from March 2014 to August 2014. The leaf and soil samples were collected and isolated by using Berlese funnel extraction methods. Specimens were isolated and identified according to their morphology (Balogh 1972). In the present study results clearly showed the variation in soil pH, NPK (Major Nutrients) and organic carbon among the study sites. The chemical components of the leaf litters of the plantation decreased the diversity of micro-arthropods and decomposition rate leads to low amount of carbon and other nutrients present in the soil. Moreover eucalyptus and wattle plantations decreases the availability of the ground water source to other plantations and micro-arthropods and hences affects the soil fertility. Hence, the present study suggests to minimize the growth of wattle and eucalyptus tree plantations in the natural areas which may help to reduce the decline of forests.

Keywords: micro-arthropods, assemblage, berlese funnel, morphology, NPK, nilgiris

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Authors: D. Kliaugaitė, J. K, Staniškis

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In this study tree types of multilayer gas barrier plastic packaging films were compared using life cycle assessment as a tool for resource efficient and environmentally low-impact materials selection. The first type of multilayer packaging film (PET-AlOx/LDPE) consists of polyethylene terephthalate with barrier layer AlOx (PET-AlOx) and low density polyethylene (LDPE). The second type of polymer film (PET/PE-EVOH-PE) is made of polyethylene terephthalate (PET) and co-extrusion film PE-EVOH-PE as barrier layer. And the third one type of multilayer packaging film (PET-PVOH/LDPE) is formed from polyethylene terephthalate with barrier layer PVOH (PET-PVOH) and low density polyethylene (LDPE). All of analyzed packaging has significant impact to resource depletion, because of raw materials extraction and energy use and production of different kind of plastics. Nevertheless the impact generated during life cycle of functional unit of II type of packaging (PET/PE-EVOH-PE) was about 25% lower than impact generated by I type (PET-AlOx/LDPE) and III type (PET-PVOH/LDPE) of packaging. Result revealed that the contribution of different gas barrier type to the overall environmental problem of packaging is not significant. The impact are mostly generated by using energy and materials during raw material extraction and production of different plastic materials as plastic polymers material as PE, LDPE and PET, but not gas barrier materials as AlOx, PVOH and EVOH. The LCA results could be useful in different decision-making processes, for selecting resource efficient and environmentally low-impact materials.

Keywords: life cycle assessment, polymer packaging, resource efficiency, materials extraction, polyethylene terephthalate

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Authors: Kasra Afsahi, Maryam Soheilifar, S. Hossein Hosseini

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Background: There is growing evidence that Cerebral Vascular Accident (CVA) can be a consequence of Covid-19 infection. Understanding novel treatment approaches are important in optimizing patient outcomes. Case: This case explores the use of Virtual Reality (VR) in the treatment of a 23-year-old COVID-positive female presenting with left hemiparesis in August 2020. Imaging showed right globus pallidus, thalamus, and internal capsule ischemic stroke. Conventional rehabilitation was started two weeks later, with virtual reality (VR) included. This game-based virtual reality (VR) technology developed for stroke patients was based on upper extremity exercises and functions for stroke. Physical examination showed left hemiparesis with muscle strength 3/5 in the upper extremity and 4/5 in the lower extremity. The range of motion of the shoulder was 90-100 degrees. The speech exam showed a mild decrease in fluency. Mild lower lip dynamic asymmetry was seen. Babinski was positive on the left. Gait speed was decreased (75 steps per minute). Intervention: Our game-based VR system was developed based on upper extremity physiotherapy exercises for post-stroke patients to increase the active, voluntary movement of the upper extremity joints and improve the function. The conventional program was initiated with active exercises, shoulder sanding for joint ROMs, walking shoulder, shoulder wheel, and combination movements of the shoulder, elbow, and wrist joints, alternative flexion-extension, pronation-supination movements, Pegboard and Purdo pegboard exercises. Also, fine movements included smart gloves, biofeedback, finger ladder, and writing. The difficulty of the game increased at each stage of the practice with progress in patient performances. Outcome: After 6 weeks of treatment, gait and speech were normal and upper extremity strength was improved to near normal status. No adverse effects were noted. Conclusion: This case suggests that VR is a useful tool in the treatment of a patient with covid-19 related CVA. The safety of newly developed instruments for such cases provides new approaches to improve the therapeutic outcomes and prognosis as well as increased satisfaction rate among patients.

Keywords: covid-19, stroke, virtual reality, rehabilitation

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Authors: Luísa P. Cruz-Lopes, Hugo Costa e Silva, Idalina Domingos, José Ferreira, Luís Teixeira de Lemos, Bruno Esteves

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The liquefaction process of cork based tree barks has led to an increase of interest due to its potential innovation in the lumber and wood industries. In this particular study the bark of Quercus cerris (Turkish oak) is used due to its appreciable amount of cork tissue, although of inferior quality when compared to the cork provided by other Quercus trees. This study aims to optimize alkaline catalysis liquefaction conditions, regarding several parameters. To better comprehend the possible chemical characteristics of the bark of Quercus cerris, a complete chemical analysis was performed. The liquefaction process was performed in a double-jacket reactor heated with oil, using glycerol and a mixture of glycerol/ethylene glycol as solvents, potassium hydroxide as a catalyst, and varying the temperature, liquefaction time and granulometry. Due to low liquefaction efficiency resulting from the first experimental procedures a study was made regarding different washing techniques after the filtration process using methanol and methanol/water. The chemical analysis stated that the bark of Quercus cerris is mostly composed by suberin (ca. 30%) and lignin (ca. 24%) as well as insolvent hemicelluloses in hot water (ca. 23%). On the liquefaction stage, the results that led to higher yields were: using a mixture of methanol/ethylene glycol as reagents and a time and temperature of 120 minutes and 200 ºC, respectively. It is concluded that using a granulometry of <80 mesh leads to better results, even if this parameter barely influences the liquefaction efficiency. Regarding the filtration stage, washing the residue with methanol and then distilled water leads to a considerable increase on final liquefaction percentages, which proves that this procedure is effective at liquefying suberin content and lignocellulose fraction.

Keywords: liquefaction, Quercus cerris, polyalcohol liquefaction, temperature

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Authors: Mardiati Zain, W. S. N. Rusmana, Erpomen, Malik Makmur, Ezi Masdia Putri

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Background and Aim: The leaves of the Leucaenaleucocephala tree have potential as a nitrogen source for ruminants. Leucaena leaf meal as protein supplement has been shown to improve the feed quality of ruminants. The effects of different levels of Leucaena leucocephala supplementation as substitute of concentrate on fiber digestibility and in vitro rumen fermentation characteristics were investigated. This research was conducted in vitro. The study used a randomized block design consisting of 3 treatments and 5 replications. The treatments were A. 40% rice straw ammoniated + 60% concentrate, B. 40% rice straw ammoniated + 50% concentrate + 10% Leucaena leuchephala, C. 40% rice straw ammoniated + 40% concentrate + 20% Leucaena leuchephala, Result: The results showed that the addition of Leucaena leucocephala increased the digestibility of Neutral detergent Fiber NDF and Acid Detergent Fiber (ADF) (p < 0.05). In this study, rumen NH3, propionate, amount of escape protein and total Volatyl Fatty Acid (VFA) were found increased significantly at treatment B. No significant difference was observed in acetate and butyrate production. The populations of total protozoa and methane production had significantly decreased (P < .05) in supplemented group. Conclusion: Supplementation of leuchaena leucochepala on completed feed based on ammoniated rice straw in vitro can increase fiber digestibility, VFA production and decreased protozoa pupulataion and methane production. Supplementation of 10% and 20% L. leucochepala were suitable to be used for further studies, therefore in vivo experiment is required to study the effects on animal production.

Keywords: digestibility, Leucaena leucocephala, complete feed, rice straw ammoniated

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Authors: Ageliki I. Katsarou, Andriana C. Kaliora, Antonia Chiou, Apostolos Papalois, Nick Kalogeropoulos, Nikolaos K. Andrikopoulos

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Chronic inflammation plays a pivotal role in CVD development, while phytochemicals have been shown to reduce CVD risk. Several studies have correlated olive oil consumption with CVD prevention and CVD risk reduction. However, the effect of individual olive oil macro- or micro-constituents and possible synergisms among them needs to be further elucidated. Herein, extra virgin olive oil (EVOO) lipidic and polar phenolics fractions were evaluated for their effect on inflammatory markers in cholesterol-fed rats. Oils combining different characteristics as to their polar phenolic content and lipid profile were used. Male Wistar rats were fed for 9 weeks on either a high-cholesterol diet (HCD) or a HCD supplemented with oils, either commercially available, i.e. EVOO, sunflower oil (SO), or modified as to their polar phenol content, i.e. phenolics deprived-EVOO (EVOOd), SO enriched with the EVOO phenolics (SOe). Post-intervention, aorta and blood samples were collected. HCD induced dyslipidemia, manifested by serum total cholesterol and low-density lipoprotein cholesterol elevation. Additionally, HCD resulted in higher adhesion molecules’ levels in rat aorta. In the case of E-selectin, this increase was attenuated by HCD supplementation with EVOO and EVOOd, while no alterations were observed in SO and SOe groups. No differences were observed between pairs of commercial and modified oils, indicating that oleates may be the components responsible for aorta E-selectin levels lowering. The same was true for vascular adhesion molecule-1 (VCAM-1); augmentation in cholesterol-fed animals was attenuated by EVOO and EVOOd diets, highlighting oleates effect. In addition, VCAM-1 levels were higher in SO group compared to the respective SOe, indicating that in the presence of phenolic compounds linoleic acid have become less prone to oxidation. Intercellular adhesion molecule-1 (ICAM-1) levels were higher in cholesterol-fed rats, however not affected by any of the oils supplemented during the intervention. Overall, EVOO was found superior in regulating adhesion molecule levels in rat aorta compared to SO. EVOO and EVOOd exhibited analogous effects on all adhesion molecules assessed, indicating that EVOO major constituents (oleates) improve E-selectin and VCAM-1 levels in rat aorta, independently from phenolics presence. Further research is needed to elucidate the effect of phenolics and oleates in other tissues.

Keywords: extra virgin olive oil, cholesterol-fed rats, polar phenolics, adhesion molecules

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Authors: Daniel Assefa, Engeda Dessalegn, Chetan Chauhan

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Moringa stenopetala is a socioeconomic valued tree that is widely available and cultivated in the Southern part of Ethiopia. The leaves have been traditionally used as a food source with high nutritional and medicinal values. The present work was carried out to evaluate the effect of thermal treatment on the total phenolic content, antioxidant and alpha-amylase inhibition activities of aqueous leaf extracts during maceration and different decoction time interval (5, 10 and 15 min). The total phenolic content was determined by the Folin-ciocalteu methods whereas antioxidant activities were determined by 2,2-diphenyl-1-picryl-hydrazyl(DPPH) radical scavenging, reducing power and ferrous ion chelating assays and alpha-amylase inhibition activity was determined using 3,5-dinitrosalicylic acid method. Total phenolic content ranged from 34.35 to 39.47 mgGAE/g. Decoction for 10 min extract showed ferrous ion chelating (92.52), DPPH radical scavenging (91.52%), alpha-amylase inhibition (69.06%) and ferric reducing power (0.765), respectively. DPPH, reducing power and alpha-amylase inhibition activities showed positive linear correlation (R2=0.853, R2= 0.857 and R2=0.930), respectively with total phenolic content but ferrous ion chelating activity was found to be weakly correlated (R2=0.481). Based on the present investigation, it could be concluded that major loss of total phenolic content, antioxidant and alpha-amylase inhibition activities of the crude leaf extracts of Moringa stenopetala leaves were observed at decoction time for 15 min. Therefore, to maintain the total phenolic content, antioxidant, and alpha-amylase inhibition activities of leaves, cooking practice should be at the optimum decoction time (5-10 min).

Keywords: alpha-amylase inhibition, antioxidant, Moringa stenopetala, total phenolic content

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Authors: Agata Zakrzewska, Dominik Kopeć, Adrian Ochtyra

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The growing number of new cameras, sensors, and research methods allow for a broader application of thermal data in remote sensing vegetation studies. The aim of this research was to check whether it is possible to use thermal infrared data with a spectral range (3.6-4.9 μm) obtained during the day and the night to assess the health condition of selected species of deciduous trees in an urban environment. For this purpose, research was carried out in the city center of Warsaw (Poland) in 2020. During the airborne data acquisition, thermal data, laser scanning, and orthophoto map images were collected. Synchronously with airborne data, ground reference data were obtained for 617 studied species (Acer platanoides, Acer pseudoplatanus, Aesculus hippocastanum, Tilia cordata, and Tilia × euchlora) in different health condition states. The results were as follows: (i) healthy trees are cooler than trees in poor condition and dying both in the daytime and nighttime data; (ii) the difference in the canopy temperatures between healthy and dying trees was 1.06oC of mean value on the nighttime data and 3.28oC of mean value on the daytime data; (iii) condition classes significantly differentiate on both daytime and nighttime thermal data, but only on daytime data all condition classes differed statistically significantly from each other. In conclusion, the aerial thermal data can be considered as an alternative to hyperspectral data, a method of assessing the health condition of trees in an urban environment. Especially data obtained during the day, which can differentiate condition classes better than data obtained at night. The method based on thermal infrared and laser scanning data fusion could be a quick and efficient solution for identifying trees in poor health that should be visually checked in the field.

Keywords: middle wave infrared, thermal imagery, tree discoloration, urban trees

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Authors: Arun Jyothi Bheemagani, Chakrapani Pullagummi, Anupalli Roja Rani

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Exploration of the chemical constituents of the plants and pharmacological screening may provide us the basis for the development of novel agents. Plants have provided us some of the very important life saving drugs used in the modern medicine. The aim of our work was to screen the phytochemical constituents and antimicrobial and antioxidant activities of methanol extract of leaves of Annona cherimola Mill plant from Tirumala forest, Tirupathi. It was originally called Chirimuya by the Inca people who lived where it was growing in the Andes of South America, is an edible fruit-bearing species of the genus Annona from the family Annonaceae. Annona cherimola Mill is a multipurpose tree with edible fruits and is one of the sources of the medicinal products. The antibacterial activity was measured by agar well diffusion method; the diameter of the zone of bacterial growth inhibition was measured after incubation of plates. The inhibitory effect was studied against the pathogenic bacteria (Klebsiella pneumonia, Bacillus subtilis, Staphylococcus aureus and Escherichia coli (E. coli). Antioxidant assays were also performed for the same extracts by spectrophotometric methods using known standard antioxidants as reference. The studied plant extracts were found to be very effective against the pathogenic microorganisms tested. The methanolic extract of Annona cherimola Mill from showed maximum activity against Escherichia coli and Staphylococcus aureus and the least concentration required showing the activity was 0.5mg/ml. Phytochemical screening of the plants revealed the presence of flavonoids, alkaloids, steroids and carbohydrates. Good presence of antioxidants was also found in the methanolic extracts.

Keywords: annona cherimola, phytochemicals, antioxidant and antibacterial activity, methanol extract

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Authors: Y. Cochet, A. Achim, Tom Flatman, J-C. Domec, J. Ogée, L. Wingate, Ram Oren

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It is accepted that atmospheric CO2 concentration will increase in the future. For the past 30 years, researchers have used FACE (Free-Air Carbon Dioxide Enrichment) facilities to study the development of terrestrial ecosystems under elevated CO2 (eCO2). Forest responses to eCO2 are likely to impact timber industries with potential feedbacks towards the atmosphere. The main objectives of this study were to examine whether eCO2 alone or in combination with N-fertilization alter wood properties and to identify changes in wood anatomy related to water transport. Wood disks were sampled at breast height from mature loblolly pine trees (Pinus taeda L.) harvested at the Duke FACE site (NC, USA). By measuring ring width and intra-ring changes in density (X-ray densitometry) and tracheid size (lumen and cell wall thickness) from pith to bark, the following hypotheses were tested: 1) eCO2 and N-fertilization interact positively to increase significantly above-ground primary productivity; 2) eCO2 and N-fertilization lead to a decrease in density; 3) eCO2 and N-fertilization increase lumen diameter and decrease cell wall thickness, thus affecting water transport capacity. Our results revealed a boost in earlywood tracheid production induced by eCO2 lasting a few years. The following decrease seemed to be buffered by N-fertilization. X-ray profiles did not show a marked decrease in wood density under eCO2 or N-fertilization, although there were changes in cell anatomical properties such as a reduction in cell-wall thickness and an increase in lumen diameter. If such effects of eCO2 are confirmed, forest management strategies for example N-fertilization should be redesigned.

Keywords: wood density, Duke FACE (free-air carbon dioxide enrichment), N fertilization, tree ring

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Authors: F. O. Danquah, F. Frimpong, E. Owusu Danquah, T. Frimpong, J. Adu, S. K. Amposah, P. Amankwaa-Yeboah, N. E. Amengor

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In the face of global concerns such as population increase, climate change, and limited natural resources, sustainable agriculture practices are critical for ensuring food security and environmental stewardship. The study was conducted in the Forest zones of Ghana during the major and minor seasons of 2023 cropping seasons to evaluate maize yield productivity improvement and profitability of integrating Cajanus cajan (pigeonpea) into a maize production system described as a pigeonpea-maize cropping system. This is towards an integrated soil fertility management (ISFM) with a legume shrub pigeonpea for sustainable maize production while improving smallholder farmers' resilience to climate change. A split-plot design with maize-pigeonpea (Pigeonpea-Maize intercrop – MPP and No pigeonpea/ Sole maize – NPP) and inorganic fertilizer rate (250 kg/ha of 15-15-15 N-P2O5-K2O + 250 kg/ha Sulphate of Ammonia (SoA) – Full rate (FR), 125 kg/ha of 15-15-15 N-P2O5-K2O + 125 kg/ha Sulphate of Ammonia (SoA) – Half rate (HR) and no inorganic fertilizer (NF) as control) was used as the main plot and subplot treatments respectively. The results indicated a significant interaction of the pigeonpea-maize cropping system and inorganic fertilizer rate on the growth and yield of the maize with better and similar maize productivity when HR and FR were used with pigeonpea biomass. Thus, the integration of pigeonpea and its biomass would result in the reduction of recommended fertiliser rate to half. This would improve farmers’ income and profitability for sustainable maize production in the face of climate change.

Keywords: agroforestry tree, climate change, integrated soil fertility management, resource use efficiency

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Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: Masoud Soltanialvar, Ali Bagherpour

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Documented cases of human infection with H9N2 avian influenza viruses, first detected in 1999 in Hong Kong and China, indicate that these viruses can be directly transmitted from birds to humans. In this study, we characterized the mutation in the Hemagglutinin (HA) genes and proteins that correlates with a shift in affinity of the Hemagglutinin (HA) protein from the “avian” type sialic receptors to the “human” type in 10 Iranian isolates. We delineated the genomes and receptor binding profile of HA gene of some field isolates and established their phylogenetic relationship to the other Asian H9N2 sub lineages. A total of 1200 tissue samples collected from 40 farms located in various states of Iran during 2008 – 2010 as part of a program to monitor Avian Influenza Viruses (AIV) infection. To determine the genetic relationship of Iranian viruses, the Hemagglutinin (HA) genes from ten isolates were amplified and sequenced (by RT-PCR method). Nucleotide sequences (orf) of the (HA) genes were used for phylogenetic tree construction. Deduced amino acid sequences showed the presence of L226 (234 in H9 numbering) in all ten Iranian isolates which indicates a preference to binding of α (2–6) sialic acid receptors, so these Iranian H9N2 viruses have the potential to infect human beings. These isolates showed high degree of homology with 2 human H9N2 isolates A/HK/1073/99, A/HK/1074/99. Phylogenetic analysis of showed that all the HA genes of the Iranian H9N2 viruses fall into a single group within a G1-like sublineage which had contributed as donor of six internal genes to H5N1 highly pathogenic avian influenza. The results of this study indicated that all Iranian viruses have the potential to emerge as highly pathogenic influenza virus, and considering the homology of these isolates with human H9N2 strains, it seems that the potential of these avian influenza isolates to infect human should not be overlooked.

Keywords: influenza virus, hemagglutinin, neuraminidase, Iran

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Authors: Siddique Ullah Baig, Alisha Manzoor

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The remotest, mountainous, and icy Broghil Valley is a high-profile protected area as a national park, which hosts one of the highest altitude permanent human settlements on the earth. This park hosts a distributed but diverse range of habitats. Due to a lack of infrastructures, higher altitudes, and harsh environmental conditions, poverty-stricken inhabitants mostly rely on its resources, causing ecological dis-balance. This study aims to investigate the environmental degradation of natural resources of the park based on empirical evidence from stakeholders and geoinformatics. The result shows that one-fourth of the park is a gently undulating basin dotted with water bodies / grass, and agricultural land and three fourth is entirely rugged with steep mountains and glaciers. There are virtually no forests as the arid cold tundra climate and high altitude prevent tree growth. Rapid three-decadal land cover changes have led to ecological disequilibrium of the park, narrowing the traditional diverse food base, decreasing the resilience of biodiversity and local livelihoods as crop-land has shifted towards fallow, alpine-grass to peat-land and snow/glacial ice area to bare-soil/rocks. The local community believes in exploiting whatever vegetation or organic material is available for use as food, fodder, and fuel. The permanent presence of the community and limited cost-effective options in the park will be a challenge forever to maintain undisturbed natural processes as the objective of a national park.

Keywords: Broghil National Park, natural resources, environmental degradation, land cover

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Authors: Sebaa H., Cherifi F., Djabeur Abderrezak M.

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Argania spinosa, Sapotaceae sole representative in Algeria and Morocco; hence it is endemic in these regions. However, it is a recognised oil, forage, and timber tree highly adapted to aridity. The exploitation of the argan fruits produces considerable amounts of under or related products. These products, such as the endocarps of a fruit, recuperated after the use of kernels to extract oil. This research studies in detail the contents of total phenolic content was determined by Folin Ciocalteu reagent and Flavonoids by aluminum chloride colorimetric assay). Antioxidant activity of extracts was expressed as the percentage of DPPH radical inhibition and IC50 values (μg/mL). Antimicrobial activity evaluated using agar disk diffusion method against reference Pseudomonas aeruginosa ATTC 27453, Escherichia coli ATCC 23922. Immature endocarps showed a higher polyphenol content than mature endocarps. The total phenolic content in immature endocarps was found to vary from 983,75+ /- 0.45 to 980,1 +/- 0.43 mg gallic acid equivalents/g dry weight, whereas in mature endocarps, the polyphenol content ranged from 100,58 mg/g +/- 0.42 to 105 +/- 0.55% mg gallic acid equivalent / g dry weight. The flavonoid content was 16.5 mg equivalent catechin/g dry weight and 9.81mg equivalent catechin /g dry weight for immature and mature endocarp fruits, respectively. DPPH assay of the endocarps extract yielded a half-maximal effective concentration (IC50) value in the immature endocarps (549.33 μg/mL) than in mature endocarps (322 μg/mL). This result can be attributed to the higher phenolics and flavonoid compounds in the immature endocarps. Methanol extract of immature endocarps exhibited antibacterial activity against E.colie (inhibition zone, 11mm).

Keywords: antioxidant activity, antimicrobial activity, total phenolic content, DPPH assay

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Authors: Abdullah Alaklabi, Ibrahim A. Arif, Sameera O. Bafeel, Ahmad H. Alfarhan, Anis Ahamed, Jacob Thomas, Mohammad A. Bakir

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Diospyros mespiliformis (Hochst. ex A.DC.; Ebenaceae) is a large deciduous medicinal plant. This plant species is currently listed as endangered in Saudi Arabia. Molecular identification of this plant species based on short sequence regions (571 and 664 bp) of plastid rbcL (ribulose-1, 5-biphosphate carboxylase) gene was investigated in this study. The endangered plant specimens were collected from Al-Baha, Saudi Arabia (GPS coordinate: 19.8543987, 41.3059349). Phylogenetic tree inferred from the rbcL gene sequences showed that this species is very closely related with D. brandisiana. The close relationship was also observed among D. bejaudii, D. Philippinensis and D. releyi (≥99.7% sequence homology). The partial rbcL gene sequence region (571 bp) that was amplified by rbcL primer-pair rbcLaF-rbcLaR failed to discriminate D. mespiliformis from the closely related plant species, D. brandisiana. In contrast, primer-pair rbcL1F-rbcL724R yielded longer amplicon, discriminated the species from D. brandisiana and demonstrated nucleotide variations in 3 different sites (645G>T; 663A>C; 710C>G). Although D. mespiliformis (EU980712) and D. brandisiana (EU980656) are very closely related species (99.4%); however, studied specimen showed 100% sequence homology with D. mespiliformis and 99.6% with D. brandisiana. The present findings showed that rbcL short sequence region (664 bp) of plastid rbcL gene, amplified by primer-pair rbcL1F-rbcL724R, can be used for authenticating samples of D. mespiliforformis and may provide help in authentic identification and management process of this medicinally valuable endangered plant species.

Keywords: Diospyros mespiliformis, endangered plant, identification partial rbcL

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Authors: Ezzat Abd El Lateef

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Agroforestry means combining the management of trees with productive agricultural activities, especially in semiarid regions where crop yield increases are limited in agroforestry systems due to the fertility and microclimate improvements and the large competitive effect of trees with crops for water and nutrients, in order to assess the effect of agroforestry of some field crops with citrus trees as an approach to establish biodiversity in fruit tree plantations. Three field crops, i.e., maize, soybean and sunflower, were inter-planted with seedless orange trees (4*4 m) or were planted as solid plantings. The results for the trees indicated a larger fruit yield was obtained when soybean and sunflowers were interplant with citrus. Statistically significant effects (P<0.05) were found for maize grain and biological yields, with increased yields when grown as solid planting. There were no differences in the yields of soya bean and sunflower, where the yields were very similar between the two cropping systems. It is evident from the trials that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Maize, unlike the other crops, was more sensitive to shade conditions under agroforestry practice and not preferred in the biodiversity system. The potential of agroforestry to improve or increase biodiversity is efficient as the understorey crops are usually C4 species, and the overstorey trees are invariably C3 species in agroforestry. Improvement in interplant species is most likely if the understorey crop is a C3 species, which are usually light saturated in the open, and partial shade may have little effect on assimilation or by a concurrent reduction in transpiration. It could be concluded that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Some field crops could be employed successfully, like soybean or sunflowers, while others like maize are sensitive to incorporate in agroforestry system.

Keywords: agroforestry, field crops, C3 and C4 plants, yield

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Authors: Anjali Roy, Mirza S. Baig

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Atherosclerosis is a chronic inflammatory disease characterized by the formation of lipid rich plaque enriched with necrotic core, modified lipid accumulation, smooth muscle cells, endothelial cells, leucocytes and macrophages. Macrophage foam cells play a critical role in the occurrence and development of inflammatory atherosclerotic plaque. Foam cells are the fat-laden macrophages in the initial stage atherosclerotic lesion formation. Foam cells are an indication of plaque build-up, or atherosclerosis, which is commonly associated with increased risk of heart attack and stroke as a result of arterial narrowing and hardening. The mechanisms that drive atherosclerotic plaque progression remain largely unknown. Dissecting the molecular mechanism involved in process of macrophage foam cell formation will help to develop therapeutic interventions for atherosclerosis. To investigate the mechanism, we studied the role of nitric oxide synthase 1(NOS1)-mediated nitric oxide (NO) on low-density lipoprotein (LDL) uptake by bone marrow derived macrophages (BMDM). Using confocal microscopy, we found that incubation of macrophages with NOS1 inhibitor, TRIM (1-(2-Trifluoromethylphenyl) imidazole) or L-NAME (N omega-nitro-L-arginine methyl ester) prior to LDL treatment significantly reduces the LDL uptake by BMDM. Further, addition of NO donor (DEA NONOate) in NOS1 inhibitor treated macrophages recovers the LDL uptake. Our data strongly suggest that NOS1 derived NO regulates LDL uptake by macrophages and foam cell formation. Moreover, we also checked proinflammatory cytokine mRNA expression through real time PCR in BMDM treated with LDL and copper oxidized LDL (OxLDL) in presences and absences of inhibitor. Normal LDL does not evoke cytokine expression whereas OxLDL induced proinflammatory cytokine expression which significantly reduced in presences of NOS1 inhibitor. Rapid NOS-1-derived NO and its stable derivative formation act as signaling agents for inducible NOS-2 expression in endothelial cells, leading to endothelial vascular wall lining disruption and dysfunctioning. This study highlights the role of NOS1 as critical players of foam cell formation and would reveal much about the key molecular proteins involved in atherosclerosis. Thus, targeting NOS1 would be a useful strategy in reducing LDL uptake by macrophages at early stage of disease and hence dampening the atherosclerosis progression.

Keywords: atherosclerosis, NOS1, inflammation, oxidized LDL

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Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev

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Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.

Keywords: lexicon of disasters, modelling, Petri nets, text annotation, social disasters

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Authors: Barış Ozluoymak, Emin Guzel, Ahmet İnce

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Since chemical fertilizers are used for meeting the deficiency of plant nutrients, its many harmful effects are not taken into consideration for the structure of the earth. These fertilizers are hampering the work of the organisms in the soil immediately after thrown to the ground. This interference is first started with a change of the soil pH and micro organismic balance is disrupted by reaction in the soil. Since there can be no fragmentation of plant residues, organic matter in the soil will be increasingly impoverished in the absence of micro organismic living. Biological activity reduction brings about a deterioration of the soil structure. If the chemical fertilization continues intensively, soils will get worse every year; plant growth will slow down and stop due to the intensity of chemical fertilizers, yield decline will be experienced and farmer will not receive an adequate return on his investment. In this research, a prototype of automatic farm manure spreading machine for orange orchards that not just manufactured in Turkey was designed, constructed, tested and eliminate the human drudgery involved in spreading of farm manure in the field. The machine comprised several components as a 5 m3 volume hopper, automatic controlled hydraulically driven chain conveyor device and side delivery conveyor belts. To spread the solid farm manure automatically, the machine was equipped with an electronic control system. The hopper and side delivery conveyor designs fitted between orange orchard tree row spacing. Test results showed that the control system has significant effects on reduction in the amount of unnecessary solid farm manure use and avoiding inefficient manual labor.

Keywords: automatic control system, conveyor belt application, orchard, solid farm manure

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Authors: Gulfam Hasan, Ijaz Ashraf, Saleem Ashraf, Muhammad Rafay Muzammil, Salman Asghar, Shafiq-Ur-Rehman Zia

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The word “climate change” has become the most popular term when anyone observes any uncertain climate variation in their respective region. Asian countries are more prone to the impact of this phenomenon, and Pakistan is the leading affected country. Last few years, governments all over the world have been trying to cater to this issue for the best entrust of their population, especially agriculture. Now the farmers in Pakistan are fully aware of the term “climate change” and are more concerned about its solutions. On the other hand, developed countries like the USA are setting a benchmark for developing countries in every sphere of life. Based on cultural and other variations, the research was carried out to identify the behavior of farmers regarding the same issue. Cross-sectional survey research was designed for an in-depth study of relevant research questions. Face-to-face interviews were conducted in Pakistan, while virtual and face-to-face interviews were conducted in the Indiana State of the USA. The results of the present study and the responses of farmers were very interesting. The common climate change mitigation strategies suggested by farmers of both countries were less use of motor vehicles (replacement with bicycles in the circle of 10 Km), less dependency on chemical fertilizers (increased use of Manure, Bio-fertilizer, Compost), and plantation of the tree. The difference of opinion was in less government interest, lack of farmers’ education, political instability (views of Pakistani farmers), awareness of local communities, self-satisfaction, and economic disparities (views of USA farmers). Based on the given evidence, it was recommended that there is a dire need to address the climate change issue all over the world without discrimination of race, color, region, or religion. Because it will affect not only agriculture but also the real effect will be on HUMANITY.

Keywords: climate change, mitigation strategies, forests, biodiversity

Procedia PDF Downloads 126

Authors: P. J. Kagosi, M. Mndolwa, E. Japhate

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The study was conducted to communities adjacent MNR, Lushoto district, Tanzania. The MNR is one of the nine nature reserves in the Eastern Arc Mountains of Tanzania with an area of 8,700ha with high biological diversity. However, biodiversity in MNR have been threatened by increasing human activities for livelihood in 1970s. The AF systems in the study area was practised since 1980s however, no study was conducted on AF impacts. This paper presents the influence of AF on livelihood of communities adjacent MNR and biodiversity conservation. Qualitative and quantitative data were collected using socio-economic survey and botanical surveys. Data were analysed using Statistical Packages for Social Sciences and content analysis. The study found that in 1970s free livestock grazing caused considerable surface runoff, soil erosion and reduction of crop production. Since 1980s, the study area received various interventions based on the land conservations and improved livelihood through practising AF systems. It was further found that the AF farming improved crop productivity, reduced soil erosion, increased firewood (80.2%) and other forest products availability and AF encouraged community members practicing indoor livestock keeping.The dominant agroforestry tree found in the study area is grevillea reported by 74.1% of respondents planting an average of 40 trees. The study found that the AF reduced pressure to MNR as forest products and fodders were obtained from community's farms in turn, currently water flow from MNR has been increased. Thus AF products support livelihood needs and conserve biodiversity. The study recommends continuity education on new AF technology packages.

Keywords: impact of agroforestry, biodiversity management, communities’ livelihoods, Magamba nature reserve

Procedia PDF Downloads 355

Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

Procedia PDF Downloads 39

Authors: B. Niez, B. Moulia, J. Dlouha, E. Badel

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Trees adjust their development to the environmental conditions they experience. Storms events of last decades showed that acclimation of trees to mechanical stresses due to wind is a very important process that allows the trees to sustain for long years. In the future, trees will experience new wind patterns, namely, more often strong winds and fewer daily moderate winds. Moreover, these patterns will go along with drought periods that may interact with the capacity of trees to adjust their growth to mechanical stresses due to wind. It is necessary to understand the mechanisms of wood functional acclimations to environmental conditions in order to predict their behaviour and in order to give foresters and breeders the relevant tools to adapt their forest management. This work aims to study how trees adjust the mechanical and hydraulic functions of their wood to environmental stresses and how this acclimation may be beneficial for the tree to resist to future stresses. In this work, young poplars were grown under controlled climatic conditions that include permanent environmental stress (daily mechanical stress of the stem by bending and/or hydric stress). Then, the properties of wood formed under these stressed conditions were characterized. First, hydraulic conductivity and sensibility to cavitation were measured at the tissue level in order to evaluate the changes in water transport capacity. Secondly, bending tests and Charpy impact tests were carried out at the millimetric scale to locally measure mechanical parameters such as elastic modulus, elastic limit or rupture energy. These experimental data allow evaluating the impacts of mechanical and water stress on the wood material. At the stem level, they will be merged in an integrative model in order to evaluate the beneficial aspect of wood acclimation for trees.

Keywords: acclimation, environmental stresses, hydraulics, mechanics, wood

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Authors: Svetlana S. Saveysheva, Victoria E. Vasilenko

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The purpose of the research was to study the emotional and personal characteristics of preschool children in relation to the characteristics of child-parent interaction and deviant parental attitudes. The study involved 172 mothers and 172 children (85 boys and 87 girls) aged 4,5 to 7 years (mean age 6 years) living in St. Petersburg, Russia. Methods used were, demographic questionnaire, projective drawing method 'House-Tree-Man', Test of anxiety (Temml, Dorki, Amen), technique of studying self-esteem 'Ladder', expert evaluation of sociability and aggressiveness, questionnaire for children-parent emotional interaction (E.I. Zaharova) and questionnaire 'Analysis of family relationships' (E.G. Eidemiller, V.V. Yustitsky). Results. The greatest number of links with personal characteristics have received such parental deviant attitudes as overprotection and characteristics of authoritarian style (prohibitions, sanctions). If the mother has such peculiarities of the parental relationship, the child is characterized by lower self-esteem, increased anxiety, distrust of themselves and hostility. Children have more pronounced manifestations of aggression in a conniving and unstable style of parenting. The sensitivity of the mother is positively associated with children’s self-esteem. Unconditional acceptance of the child, the predominance of a positive emotional background, orientation to the state of the child during interaction promote the development of communication skills and reduce of aggressiveness. But the excessive closeness of the mother with the child can make it difficult to develop the communicative skills. Conclusions. The greatest influence on emotional and personal characteristics is provided by such features of the parental relation as overprotection, characteristics of authoritarian style, underdevelopment of the sphere of parental feelings, sensitivity of mother and behavioral manifestations of emotional interaction. Research is supported by RFBR №18-013-00990.

Keywords: characteristics of personality, child-parent interaction, children, deviant parental attitudes

Procedia PDF Downloads 238

Authors: Kehabtimer Shiferaw Kotiso, Getachew Hailemariam, Abiy Seifu Estifanos

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Introduction: Despite the highest share of low birth weight (LBW) for neonatal mortality and morbidity, predicting births with LBW for better intervention preparation is challenging. This study aims to predict LBW using a dataset encompassing 53,637 birth cohorts collected from 36 primary hospitals across seven regions in Ethiopia from February 2022 to June 2024. Methods: We identified ten explanatory variables related to maternal and neonatal characteristics, including maternal education, age, residence, history of miscarriage or abortion, history of preterm birth, type of pregnancy, number of livebirths, number of stillbirths, antenatal care frequency, and sex of the fetus to predict LBW. Using WEKA 3.8.2, we developed and compared seven machine learning algorithms. Data preprocessing included handling missing values, outlier detection, and ensuring data integrity in birth weight records. Model performance was evaluated through metrics such as accuracy, precision, recall, F1-score, and area under the Receiver Operating Characteristic curve (ROC AUC) using 10-fold cross-validation. Results: The results demonstrated that the decision tree, J48, logistic regression, and gradient boosted trees model achieved the highest accuracy (94.5% to 94.6%) with a precision of 93.1% to 93.3%, F1-score of 92.7% to 93.1%, and ROC AUC of 71.8% to 76.6%. Conclusion: This study demonstrates the effectiveness of machine learning models in predicting LBW. The high accuracy and recall rates achieved indicate that these models can serve as valuable tools for healthcare policymakers and providers in identifying at-risk newborns and implementing timely interventions to achieve the sustainable developmental goal (SDG) related to neonatal mortality.

Keywords: low birth weight, machine learning, classification, neonatal mortality, Ethiopia

Procedia PDF Downloads 25

Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

Procedia PDF Downloads 448

Authors: Kherbache Mehdi

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Within the framework of the validation of the Master in business administration marketing and sales in INSIM institute international in management Blida, we get the opportunity to do a professional internship in Sonelgaz Enterprise and a thesis. The thesis deals with the integration of social networking in the communication strategy of a company. The problematic is: How communicate with social network can be a solution for companies? The challenges stressed by this thesis were to suggest limits and recommendations to Sonelgaz Enterprise concerning social networks. The whole social networks represent more than a billion people as a potential target for the companies. Thanks to research and a qualitative approach, we have identified tree valid hypothesis. The first hypothesis allows confirming that using social networks cannot be ignored by any company in its communication strategy. However, the second hypothesis demonstrates that it’s necessary to prepare a strategy that integrates social networks in the communication plan of the company. The risk of this strategy is very limited because failure on social networks is not a restraint for the enterprise, social networking is not expensive and, a bad image which could result from it is not as important in the long-term. Furthermore, the return on investment is difficult to evaluate. Finally, the last hypothesis shows that firms establish a new relation between consumers and brands thanks to the proximity allowed by social networks. After the validation of the hypothesis, we suggested some recommendations to Sonelgaz Enterprise regarding the communication through social networks. Firstly, the company must use the interactivity of social network in order to have fruitful exchanges with the community. We also recommended having a strategy to treat negative comments. The company must also suggest delivering resources to the community thanks to a community manager, in order to have a good relation with the community. Furthermore, we advised using social networks to do business intelligence. Sonelgaz Enterprise can have some creative and interactive contents with some amazing applications on Facebook for example. Finally, we recommended to the company to be not intrusive with “fans” or “followers” and to be open to all the platforms: Twitter, Facebook, Linked-In for example.

Keywords: social network, buzz, communication, consumer, return on investment, internet users, web 2.0, Facebook, Twitter, interaction

Procedia PDF Downloads 423

Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

Procedia PDF Downloads 143