Search results for: guava leaf extract
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2628

Search results for: guava leaf extract

738 Collective Intelligence-Based Early Warning Management for Agriculture

Authors: Jarbas Lopes Cardoso Jr., Frederic Andres, Alexandre Guitton, Asanee Kawtrakul, Silvio E. Barbin

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The important objective of the CyberBrain Mass Agriculture Alarm Acquisition and Analysis (CBMa4) project is to minimize the impacts of diseases and disasters on rice cultivation. For example, early detection of insects will reduce the volume of insecticides that is applied to the rice fields through the use of CBMa4 platform. In order to reach this goal, two major factors need to be considered: (1) the social network of smart farmers; and (2) the warning data alarm acquisition and analysis component. This paper outlines the process for collecting the warning and improving the decision-making result to the warning. It involves two sub-processes: the warning collection and the understanding enrichment. Human sensors combine basic suitable data processing techniques in order to extract warning related semantic according to collective intelligence. We identify each warning by a semantic content called 'warncons' with multimedia metaphors and metadata related to these metaphors. It is important to describe the metric to measuring the relation among warncons. With this knowledge, a collective intelligence-based decision-making approach determines the action(s) to be launched regarding one or a set of warncons.

Keywords: agricultural engineering, warning systems, social network services, context awareness

Procedia PDF Downloads 356
737 Performance Comparison of Outlier Detection Techniques Based Classification in Wireless Sensor Networks

Authors: Ayadi Aya, Ghorbel Oussama, M. Obeid Abdulfattah, Abid Mohamed

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Nowadays, many wireless sensor networks have been distributed in the real world to collect valuable raw sensed data. The challenge is to extract high-level knowledge from this huge amount of data. However, the identification of outliers can lead to the discovery of useful and meaningful knowledge. In the field of wireless sensor networks, an outlier is defined as a measurement that deviates from the normal behavior of sensed data. Many detection techniques of outliers in WSNs have been extensively studied in the past decade and have focused on classic based algorithms. These techniques identify outlier in the real transaction dataset. This survey aims at providing a structured and comprehensive overview of the existing researches on classification based outlier detection techniques as applicable to WSNs. Thus, we have identified key hypotheses, which are used by these approaches to differentiate between normal and outlier behavior. In addition, this paper tries to provide an easier and a succinct understanding of the classification based techniques. Furthermore, we identified the advantages and disadvantages of different classification based techniques and we presented a comparative guide with useful paradigms for promoting outliers detection research in various WSN applications and suggested further opportunities for future research.

Keywords: bayesian networks, classification-based approaches, KPCA, neural networks, one-class SVM, outlier detection, wireless sensor networks

Procedia PDF Downloads 474
736 Hair Regrowth Effect of Herbal Formula on Androgenic Alopecia Rat Model

Authors: Jian-You Wang, Feng Yi Hsu, Chieh-Hsi Wu

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Androgenetic alopecia (AGA) is an androgen-dependent disorder caused by excess testosterone in blood capillaries or excess enzyme activity of 5α- reductase in hair follicles. Plants, alone or in combination, have been widely used for hair growth promotion since ancient times in Asia. In this study, the efficacy of a traditional Chinese herbal formula, Shen-Ying-Yang-Zhen-Dan (SYYZD) with different kinds of extract solvents, facilitating hair regrowth in testosterone-induced hair loss have been determined. The study was performed by treating with either 95 % ethanol aqueous extracts, 50% ethanol aqueous extracts or deionized water extracts orally in four-week-old male S.D. rats that experienced hair regrowth interruption induced by testosterone treatment. The 50% ethanol aqueous extracts group showed better hair regrowth promotion activities than either 95% ethanol aqueous extracts or deionized water extracts groups in 14 days treatment. In conclusion, our results suggest that 50% ethanol aqueous SYYZD extracts have hair growth promoting potential and may be beneficial as an alternative medicine for androgenetic alopecia treatment.

Keywords: Shen-Ying-Yang-Zhen-Dan, androgenic alopecia, hair loss, hair growth promotion, hair regrowth effect

Procedia PDF Downloads 759
735 Toxic Heavy Metal Accumulation by Algerian Malva sylvestris L. Depending on Location Variation

Authors: Souhila Terfi, Fatma Hassaine-Sadi

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In the present study, wet digestion with HCl and HNO3 mixture was used to extract the heavy metals (copper (Cu), chromium (Cr), zinc (Zn), lead (Pb) and cadmium (Cd)) from the leaves, the stems and the roots of Malva sylvestris L., which were subsequently analyzed by AAS. The samples (soil and parts of species) were collected from different sites: the industrial area (IA) (Rouiba), the rubbish dump area (RDA) (Boudouaou), the residential area (RA) with large open fields and construction activities (Blida), the Montaigne area (MA) (Chrea) and the high plateau area (HPA) (Berouaguia). The study showed differences in metal concentrations according to the analysed parts and the different sampling locations. In the contaminated site of the industrial area (IA), high content of the toxic heavy metals (Cd: 3.18 µg/g DW and Pb: 34.48 µg/g DW) were found in the leaves of Malva sylvestris L. This finding suggests that the consumers of this species could be exposed to a risk associated with this higher level of these toxic metals. It was found that Malva sylvestris L. is rich by Zn and Cu in some sites, which are considered to be the essential elements for the human health. The obtained results with the control site (Montaigne area) suggest that this species can be applicable in both the health and food, feasible alternatives as medicinal plant without any risk.

Keywords: Malva sylvestris L., toxic heavy metal, medicinal plant, impact on human health

Procedia PDF Downloads 339
734 The Effects of Drought and Nitrogen on Soybean (Glycine max (L.) Merrill) Physiology and Yield

Authors: Oqba Basal, András Szabó

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Legume crops are able to fix atmospheric nitrogen by the symbiotic relation with specific bacteria, which allows the use of the mineral nitrogen-fertilizer to be reduced, or even excluded, resulting in more profit for the farmers and less pollution for the environment. Soybean (Glycine max (L.) Merrill) is one of the most important legumes with its high content of both protein and oil. However, it is recommended to combine the two nitrogen sources under stress conditions in order to overcome its negative effects. Drought stress is one of the most important abiotic stresses that increasingly limits soybean yields. A precise rate of mineral nitrogen under drought conditions is not confirmed, as it depends on many factors; soybean yield-potential and soil-nitrogen content to name a few. An experiment was conducted during 2017 growing season in Debrecen, Hungary to investigate the effects of nitrogen source on the physiology and the yield of the soybean cultivar 'Boglár'. Three N-fertilizer rates including no N-fertilizer (0 N), 35 kg ha-1 of N-fertilizer (35 N) and 105 kg ha-1 of N-fertilizer (105 N) were applied under three different irrigation regimes; severe drought stress (SD), moderate drought stress (MD) and control with no drought stress (ND). Half of the seeds in each treatment were pre-inoculated with Bradyrhizobium japonicum inoculant. The overall results showed significant differences associated with fertilization and irrigation, but not with inoculation. Increasing N rate was mostly accompanied with increased chlorophyll content and leaf area index, whereas it positively affected the plant height only when the drought was waived off. Plant height was the lowest under severe drought, regardless of inoculation and N-fertilizer application and rate. Inoculation increased the yield when there was no drought, and a low rate of N-fertilizer increased the yield furthermore; however, the high rate of N-fertilizer decreased the yield to a level even less than the inoculated control. On the other hand, the yield of non-inoculated plants increased as the N-fertilizer rate increased. Under drought conditions, adding N-fertilizer increased the yield of the non-inoculated plants compared to their inoculated counterparts; moreover, the high rate of N-fertilizer resulted in the best yield. Regardless of inoculation, the mean yield of the three fertilization rates was better when the water amount increased. It was concluded that applying N-fertilizer to provide the nitrogen needed by soybean plants, with the absence of N2-fixation process, is very important. Moreover, adding relatively high rate of N-fertilizer is very important under severe drought stress to alleviate the drought negative effects. Further research to recommend the best N-fertilizer rate to inoculated soybean under drought stress conditions should be executed.

Keywords: drought stress, inoculation, N-fertilizer, soybean physiology, yield

Procedia PDF Downloads 133
733 Photocatalytic Degradation of Toxic Phenols Using Zinc Oxide Doped Prussian Blue Nanocomposite

Authors: Rachna, Uma Shanker

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Aromatic phenols, being priority pollutants, are found in various industrial effluents and seeking the attention of environmentalists worldwide, owing to their life-threatening effects. In the present study, the coupling of zinc oxide with Prussian blue was achieved involving co-precipitation synthesis process using Azadirachta indica plant extract. The fabricated nanocatalyst was employed for the sunlight mediated photodegradation of various phenols (Phenol, 3-Aminophenol, and 2,4-Dinitrophenol). Doping of zinc oxide with Prussian blue caused an increase in the surface area to value 80.109 m²g⁻¹ and also enhanced the semiconducting tendency of the nanocomposite with band gap energy 1.101 eV. The experiment was performed at different parameters of phenols concentration, catalyst amount, pH, time, and exposure of sunlight. The obtained results showed a lower elimination of 2,4-DNP (93%) than 3-AP (97%) and phenol (95%) owing to their molecular weight and basicity differences. In comparison to the starting material (zinc oxide and Prussian blue), nanocomposite was more capable in degrading the phenols and lowered the t1/2 value of phenol (4.405 h), 3-AP (4.04 h) and 2,4-DNP (4.68 h) to a greater extent. Effect of different foreign anions was also studied to check nanocomposite’s liability under natural conditions. The extent of charge recombination being the most limiting factor in the photodegradation of pollutants was determined through the photoluminescence. Sunlight active ZnO@FeHCF nanocomposite was proven to exhibit good catalytic ability up to 10 cycles.

Keywords: nanocomposite, phenols, photodegradation, sunlight, water

Procedia PDF Downloads 108
732 Meeting India's Energy Demand: U.S.-India Energy Cooperation under Trump

Authors: Merieleen Engtipi

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India's total share of global population is nearly 18%; however, its per capita energy consumption is only one-third of global average. The demand and supply of electricity are uneven in the country; around 240 million of the population have no access to electricity. However, with India's trajectory for modernisation and economic growth, the demand for energy is only expected to increase. India is at a crossroad, on the one hand facing the increasing demand for energy and on the other hand meeting the Paris climate policy commitments, and further the struggle to provide efficient energy. This paper analyses the policies to meet India’s need for energy, as the per capita energy consumption is likely to be double in 6-7 years period. Simultaneously, India's Paris commitment requires curbing of carbon emission from fossil fuels. There is an increasing need for renewables to be cheaply and efficiently available in the market and for clean technology to extract fossil fuels to meet climate policy goals. Fossil fuels are the most significant generator of energy in India; with the Paris agreement, the demand for clean energy technology is increasing. Finally, the U.S. decided to withdraw from the Paris Agreement; however, the two countries plan to continue engaging bilaterally on energy issues. The U.S. energy cooperation under Trump administration is significantly vital for greater energy security, transfer of technology and efficiency in energy supply and demand.

Keywords: energy demand, energy cooperation, fossil fuels, technology transfer

Procedia PDF Downloads 235
731 Recommender Systems Using Ensemble Techniques

Authors: Yeonjeong Lee, Kyoung-jae Kim, Youngtae Kim

Abstract:

This study proposes a novel recommender system that uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user’s preference. The proposed model consists of two steps. In the first step, this study uses logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. Then, this study combines the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. In the second step, this study uses the market basket analysis to extract association rules for co-purchased products. Finally, the system selects customers who have high likelihood to purchase products in each product group and recommends proper products from same or different product groups to them through above two steps. We test the usability of the proposed system by using prototype and real-world transaction and profile data. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The results also show that the proposed system may be useful in real-world online shopping store.

Keywords: product recommender system, ensemble technique, association rules, decision tree, artificial neural networks

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730 Soil Compaction by a Forwarder in Timber Harvesting

Authors: Juang R. Matangaran, Erianto I. Putra, Iis Diatin, Muhammad Mujahid, Qi Adlan

Abstract:

Industrial plantation forest is the producer of logs in Indonesia. Several companies of industrial plantation forest have been successfully planted with fast-growing species, and it entered their annual harvesting period. Heavy machines such as forwarders are used in timber harvesting to extract logs from stump to landing site. The negative impact of using such machines are loss of topsoil and soil compaction. Compacted soil is considered unfavorable for plant growth. The research objectives were to analyze the soil bulk density, rut, and cone index of the soil caused by a forwarder passes, to analyze the relation between several times of forwarder passes to the increase of soil bulk density. A Valmet forwarder was used in this research. Soil bulk density at soil surface and cone index from the soil surface to the 50 cm depth of soil were measured at the harvested area. The result showed that soil bulk density increase with the increase of the Valmet forwarder passes. Maximum soil bulk density occurred after 5 times forwarder Valmet passed. The cone index tended to increase from the surface until 50 cm depth of soil. Rut formed and high soil bulk density indicated the soil compaction occurred by the forwarder operation.

Keywords: bulk density, forwarder Valmet, plantation forest, soil compaction, timber harvesting

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729 Seed Priming Treatments in Common Zinnia (Zinnia elegans) Using Some Plant Extracts

Authors: Atakan Efe Akpınar, Zeynep Demir

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Seed priming technologies are frequently used nowadays to increase the germination potential and stress tolerance of seeds. These treatments might be beneficial for native species as well as crops. Different priming treatments can be used depending on the type of plant, the morphology, and the physiology of the seed. Moreover, these may be various physical, chemical, and/or biological treatments. Aiming to improve studies about seed priming, ideas need to be brought into this technological sector related to the agri-seed industry. This study addresses the question of whether seed priming with plant extracts can improve seed vigour and germination performance. By investigating the effects of plant extract priming on various vigour parameters, the research aims to provide insights into the potential benefits of this treatment method. Thus, seed priming was carried out using some plant extracts. Firstly, some plant extracts prepared from plant leaves, roots, or fruit parts were obtained for use in priming treatments. Then, seeds of Common zinnia (Zinnia elegans) were kept in solutions containing plant extracts at 20°C for 48 hours. Seeds without any treatment were evaluated as the control group. At the end of priming applications, seeds are dried superficially at 25°C. Seeds of Common zinnia (Zinnia elegans) were analyzed for vigour (normal germination rate, germination time, germination index etc.). In the future, seed priming applications can expand to multidisciplinary research combining with digital, bioinformatic and molecular tools.

Keywords: seed priming, plant extracts, germination, biology

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728 Image Multi-Feature Analysis by Principal Component Analysis for Visual Surface Roughness Measurement

Authors: Wei Zhang, Yan He, Yan Wang, Yufeng Li, Chuanpeng Hao

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Surface roughness is an important index for evaluating surface quality, needs to be accurately measured to ensure the performance of the workpiece. The roughness measurement based on machine vision involves various image features, some of which are redundant. These redundant features affect the accuracy and speed of the visual approach. Previous research used correlation analysis methods to select the appropriate features. However, this feature analysis is independent and cannot fully utilize the information of data. Besides, blindly reducing features lose a lot of useful information, resulting in unreliable results. Therefore, the focus of this paper is on providing a redundant feature removal approach for visual roughness measurement. In this paper, the statistical methods and gray-level co-occurrence matrix(GLCM) are employed to extract the texture features of machined images effectively. Then, the principal component analysis(PCA) is used to fuse all extracted features into a new one, which reduces the feature dimension and maintains the integrity of the original information. Finally, the relationship between new features and roughness is established by the support vector machine(SVM). The experimental results show that the approach can effectively solve multi-feature information redundancy of machined surface images and provides a new idea for the visual evaluation of surface roughness.

Keywords: feature analysis, machine vision, PCA, surface roughness, SVM

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727 Variation of Streamwise and Vertical Turbulence Intensity in a Smooth and Rough Bed Open Channel Flow

Authors: M. Abdullah Al Faruque, Ram Balachandar

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An experimental study with four different types of bed conditions was carried out to understand the effect of roughness in open channel flow at two different Reynolds numbers. The bed conditions include a smooth surface and three different roughness conditions which were generated using sand grains with a median diameter of 2.46 mm. The three rough conditions include a surface with distributed roughness, a surface with continuously distributed roughness and a sand bed with a permeable interface. A commercial two-component fibre-optic LDA system was used to conduct the velocity measurements. The variables of interest include the mean velocity, turbulence intensity, the correlation between the streamwise and the wall normal turbulence, Reynolds shear stress and velocity triple products. Quadrant decomposition was used to extract the magnitude of the Reynolds shear stress of the turbulent bursting events. The effect of roughness was evident throughout the flow depth. The results show that distributed roughness has the greatest roughness effect followed by the sand bed and the continuous roughness. Compared to the smooth bed, the streamwise turbulence intensity reduces but the vertical turbulence intensity increases at a location very close to the bed due to the introduction of roughness. Although the same sand grain is used to create the three different rough bed conditions, the difference in the turbulence intensity is an indication that the specific geometry of the roughness has an influence on turbulence structure.

Keywords: open channel flow, smooth and rough bed, Reynolds number, turbulence

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726 Profiling the Volatile Metabolome in Pear Leaves with Different Resistance to the Pear Psylla Cacopsylla bidens (Sulc) and Characterization of Phenolic Acid Decarboxylase

Authors: Mwafaq Ibdah, Mossab, Yahyaa, Dor Rachmany, Yoram Gerchman, Doron Holland, Liora Shaltiel-Harpaz

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Pear Psylla is the most important pest of pear in all pear-growing regions, in Asian, European, and the USA. Pear psylla damages pears in several ways: high-density populations of these insects can cause premature leaf and fruit drop, diminish plant growth, and reduce fruit size. In addition, their honeydew promotes sooty mold on leaves and russeting on fruit. Pear psyllas are also considered vectors of pear pathogens such as Candidatus Phytoplasma pyri causing pear decline that can lead to loss of crop and tree vigor, and sometimes loss of trees. Psylla control is a major obstacle to efficient integrated pest management. Recently we have identified two naturally resistance pear accessions (Py.760-261 and Py.701-202) in the Newe Ya’ar live collection. GC-MS volatile metabolic profiling identified several volatile compounds common in these accessions but lacking, or much less common, in a sensitive accession, the commercial Spadona variety. Among these volatiles were styrene and its derivatives. When the resistant accessions were used as inter-stock, the volatile compounds appear in commercial Spadona scion leaves, and it showed reduced susceptibility to pear psylla. Laboratory experiments and applications of some of these volatile compounds were very effective against psylla eggs, nymphs, and adults. The genes and enzymes involved in the specific reactions that lead to the biosynthesis of styrene in plant are unknown. We have identified a phenolic acid decarboxylase that catalyzes the formation of p-hydroxystyrene, which occurs as a styrene analog in resistant pear genotypes. The His-tagged and affinity chromatography purified E. coli-expressed pear PyPAD1 protein could decarboxylate p-coumaric acid and ferulic acid to p-hydroxystyrene and 3-methoxy-4-hydroxystyrene. In addition, PyPAD1 had the highest activity toward p-coumaric acid. Expression analysis of the PyPAD gene revealed that its expressed as expected, i.e., high when styrene levels and psylla resistance were high.

Keywords: pear Psylla, volatile, GC-MS, resistance

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725 Establishment of a Classifier Model for Early Prediction of Acute Delirium in Adult Intensive Care Unit Using Machine Learning

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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724 Formulation and Technology of the Composition of Essential Oils as a Feed Additive in Poultry with Antibacterial Action

Authors: S. Barbaqadze, M. Goderdzishvili, E. Mosidze, L. Lomtadze, V. Mshvildadze, L. Bakuridze, D. Berashvili, A. Bakuridze

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This paper focuses on the formulation of phytobiotic designated for further implantation in poultry farming. Composition was meant to be water-soluble powder containing antibacterial essential oils. The development process involved Thyme, Monarda and Clary sage essential oils. The antimicrobial activity of essential oils composite was meant to be tested against gram-negative and gram-positive bacterial strains. The results are processed using the statistical program Sigma STAT. To make essential oils composition water soluble surfactants were added to them. At the first stage of the study, nine options for the optimal composition of essential oils and surfactants were developed. The effect of the amount of surfactants on the essential oils composition solubility in water has been investigated. On the basis of biopharmaceutical studies, the formulation of phytobiotic has been determined: Thyme, monarda and clary sage essential oils 2:1:1 - 100 parts; Licorice extract 5.25 parts and inhalation lactose 300 parts. A technology for the preparation of phytobiotic has been developed and a technological scheme for the preparation of phytobiotic has been made up. The research was performed within the framework of the grant project CARYS-19-363 funded be the Shota Rustaveli National Science Foundation of Georgia.

Keywords: clary, essential oils, monarda, phytobiotics, poultry, thyme

Procedia PDF Downloads 146
723 Comparative Effects of Homoplastic and Synthetic Pituitary Extracts on Induced Breeding of Heterobranchus longifilis (Valenciennes, 1840) in Indoor Hatchery Tanks in Owerri South East Nigeria

Authors: I. R. Keke, C. S. Nwigwe, O. S. Nwanjo, A. S. Egeruoh

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An experiment was carried out at Urban Farm and Fisheries Nigeria Ltd, Owerri Imo State South East Nigeria between February and June 2014 to induce Brood stock of Heterobranchus longifilis (mean wt 1.3kg) in concrete tanks (1.0 x 2.0 x 1.5m) in dimension using a synthetic hormone (Ovaprim) and pituitary extract from Heterobranchus longifilis. Brood stock males were selected as pituitary donors and their weights matched those of females to be injected at 1ml/kg body weight of Fish. Ovaprim, was injected at 0.5ml/kg body weight of female fish. A latency period of 12 hours was allowed after injection of the Brood stock females before stripping the egg and incubation at 23 °C. While incubating the eggs, samples were drawn and the rate of fertilization was determined. Hatching occurred within 33 hours and hatchability rate (%) was determined by counting the active hatchings. The result showed that Ovaprim injected Brood stock eggs fertilized up to 80% while the pituitary from the Heterobranchus longifilis had low fertilization and hatching success 20%. Ovaprim is imported and costly, so more effort is required to enhance the procedures for homoplastic hypophysation.

Keywords: heterobranchus longifilis, ovaprim, hypophysation, latency period, pituitary

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722 Identification of Potential Predictive Biomarkers for Early Diagnosis of Preeclampsia Growth Factors to microRNAs

Authors: Sadia Munir

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Preeclampsia is the contributor to the worldwide maternal mortality of approximately 100,000 deaths a year. It complicates about 10% of all pregnancies and is the first cause of maternal admission to intensive care units. Predicting preeclampsia is a major challenge in obstetrics. More importantly, no major progress has been achieved in the treatment of preeclampsia. As placenta is the main cause of the disease, the only way to treat the disease is to extract placental and deliver the baby. In developed countries, the cost of an average case of preeclampsia is estimated at £9000. Interestingly, preeclampsia may have an impact on the health of mother or infant, beyond the pregnancy. We performed a systematic search of PubMed including the combination of terms such as preeclampsia, biomarkers, treatment, hypoxia, inflammation, oxidative stress, vascular endothelial growth factor A, activin A, inhibin A, placental growth factor, transforming growth factor β-1, Nodal, placenta, trophoblast cells, microRNAs. In this review, we have summarized current knowledge on the identification of potential biomarkers for the diagnosis of preeclampsia. Although these studies show promising data in early diagnosis of preeclampsia, the current value of these factors as biomarkers, for the precise prediction of preeclampsia, has its limitation. Therefore, future studies need to be done to support some of the very promising and interesting data to develop affordable and widely available tests for early detection and treatment of preeclampsia.

Keywords: activin, biomarkers, growth factors, miroRNA

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721 Technical and Pedagogical Considerations in Producing Screen Recorded Videos

Authors: M. Nikafrooz, J. Darsareh

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Due to the COVID-19 pandemic, its impacts on education all over the world and the problems arising from the use of traditional methods in education, it was necessary to apply alternative solutions to achieve educational goals. In this regard, electronic content production through screen recording and giving educational services in virtual classes became popular among many teachers. But the production of screen recorded videos involves special technical and educational considerations so that educators could be able to produce valuable and well-made videos by taking those considerations into account. The purpose of this study was to extract and find the technical and educational considerations of producing screen recorded videos to provide a useful and comprehensive guideline for e-content producers to enable them to produce high-quality educational videos. This study is fundamental research and data collection has been done using the Delphi method. In this research, an attempt has been made to provide the necessary criteria and considerations regarding the design and production of screen recorded videos by studying the literatures, identifying and analyzing learners' and teachers' needs and expectations, reviewing the previously produced videos. The results of these studies led to the finding and extracting 129 indicators in the form of 6 criteria. Such considerations are expected to reduce production and editing time, increase the technical and educational quality, and finally facilitating and enhancing the processes of teaching and learning.

Keywords: e-content, screen recorded videos, screen recording software, technical and pedagogical considerations

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720 Preparation of Biomedical Hydrogels Using Phenolic Compounds and Electron Beam Irradiation

Authors: Farnaz Sadeghi, Moslem Tavakol

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In this study, an attempt has been made to prepare a physically cross-linked gel by cooling of tannic acid (TA)-polyvinyl alcohol (PVA) solution that subsequently convert to antibacterial chemically cross-linked hydrogel by using electron beam irradiation. PVA is known for its biocompatibility and hydrophilicity, and TA is known for being a natural compound which can serve as a cross-linking agent and a therapeutic agent. Swelling behavior, gel content, pore size, and mechanical properties of hydrogels which prepared at 14, 28, and 56 (kGy) with different ratios of polymers were investigated. PVA-TA hydrogel showed sustained release of tannic acid as approximately 20% and 50% of loaded TA released from the hydrogel after 4 and 72 h release time. We found that gel content decreased and the moisture retention capability increased by an increase in TA composition. In addition, PVA-TA hydrogels showed a good antibacterial activity against S.aureus. MTT analysis indicated that close to 83% of fibroblast cells remained viable after 48 h exposure to hydrogel extract. Moreover, the cooling of 10% PVA solution containing 0.5 and 0.75% w/v tannic acid to room and refrigerator, respectively, led to formation of physical gel that did not present any flow index after inversion of hydrogel cast. According to the results, the hydrogel prepared by electron beam irradiation of blended PVA-TA solution could be further investigated as a promising candidate for wound healing.

Keywords: poly vinyl alcohol, tannic acid, electron beam irradiation, hydrogel wound dressing

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719 Artificial Intelligence and Machine Vision-Based Defect Detection Methodology for Solid Rocket Motor Propellant Grains

Authors: Sandip Suman

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Mechanical defects (cracks, voids, irregularities) in rocket motor propellant are not new and it is induced due to various reasons, which could be an improper manufacturing process, lot-to-lot variation in chemicals or just the natural aging of the products. These defects are normally identified during the examination of radiographic films by quality inspectors. However, a lot of times, these defects are under or over-classified by human inspectors, which leads to unpredictable performance during lot acceptance tests and significant economic loss. The human eye can only visualize larger cracks and defects in the radiographs, and it is almost impossible to visualize every small defect through the human eye. A different artificial intelligence-based machine vision methodology has been proposed in this work to identify and classify the structural defects in the radiographic films of rocket motors with solid propellant. The proposed methodology can extract the features of defects, characterize them, and make intelligent decisions for acceptance or rejection as per the customer requirements. This will automatize the defect detection process during manufacturing with human-like intelligence. It will also significantly reduce production downtime and help to restore processes in the least possible time. The proposed methodology is highly scalable and can easily be transferred to various products and processes.

Keywords: artificial intelligence, machine vision, defect detection, rocket motor propellant grains

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718 Effect of Red Cabbage Antioxidant Extracts on Lipid Oxidation of Fresh Tilapia

Authors: Ayse Demirbas, Bruce A. Welt, Yavuz Yagiz

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Oxidation of polyunsaturated fatty acids (PUFA), eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in fish causes loss of product quality. Oxidative rancidity causes loss of nutritional value and undesirable color changes. Therefore, powerful antioxidant extracts may provide a relatively low cost and natural means to reduce oxidation, resulting in longer, higher quality and higher value shelf life of foods. In this study, we measured effects of red cabbage antioxidant on lipid oxidation in fresh tilapia filets using thiobarbituric acid reactive substances (TBARS) assay, peroxide value (PV) and color assesment analysis. Extraction of red cabbage was performed using an efficient microwave method. Fresh tilapia filets were dipped in or sprayed with solutions containing different concentrations of extract. Samples were stored for up to 9 days at 4°C and analyzed every other day for color and lipid oxidation. Results showed that treated samples had lower oxidation than controls. Lipid peroxide values on treated samples showed benefits through day-7. Only slight differences were observed between spraying and dipping methods. This work shows that red cabbage antioxidant extracts may represent an inexpensive and all natural method for reducing oxidative spoilage of fresh fish.

Keywords: antioxidant, shelf life, fish, red cabbage, lipid oxidation

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717 Application of the Total Least Squares Estimation Method for an Aircraft Aerodynamic Model Identification

Authors: Zaouche Mohamed, Amini Mohamed, Foughali Khaled, Aitkaid Souhila, Bouchiha Nihad Sarah

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The aerodynamic coefficients are important in the evaluation of an aircraft performance and stability-control characteristics. These coefficients also can be used in the automatic flight control systems and mathematical model of flight simulator. The study of the aerodynamic aspect of flying systems is a reserved domain and inaccessible for the developers. Doing tests in a wind tunnel to extract aerodynamic forces and moments requires a specific and expensive means. Besides, the glaring lack of published documentation in this field of study makes the aerodynamic coefficients determination complicated. This work is devoted to the identification of an aerodynamic model, by using an aircraft in virtual simulated environment. We deal with the identification of the system, we present an environment framework based on Software In the Loop (SIL) methodology and we use MicrosoftTM Flight Simulator (FS-2004) as the environment for plane simulation. We propose The Total Least Squares Estimation technique (TLSE) to identify the aerodynamic parameters, which are unknown, variable, classified and used in the expression of the piloting law. In this paper, we define each aerodynamic coefficient as the mean of its numerical values. All other variations are considered as modeling uncertainties that will be compensated by the robustness of the piloting control.

Keywords: aircraft aerodynamic model, total least squares estimation, piloting the aircraft, robust control, Microsoft Flight Simulator, MQ-1 predator

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716 3D Printing Perceptual Models of Preference Using a Fuzzy Extreme Learning Machine Approach

Authors: Xinyi Le

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In this paper, 3D printing orientations were determined through our perceptual model. Some FDM (Fused Deposition Modeling) 3D printers, which are widely used in universities and industries, often require support structures during the additive manufacturing. After removing the residual material, some surface artifacts remain at the contact points. These artifacts will damage the function and visual effect of the model. To prevent the impact of these artifacts, we present a fuzzy extreme learning machine approach to find printing directions that avoid placing supports in perceptually significant regions. The proposed approach is able to solve the evaluation problem by combing both the subjective knowledge and objective information. Our method combines the advantages of fuzzy theory, auto-encoders, and extreme learning machine. Fuzzy set theory is applied for dealing with subjective preference information, and auto-encoder step is used to extract good features without supervised labels before extreme learning machine. An extreme learning machine method is then developed successfully for training and learning perceptual models. The performance of this perceptual model will be demonstrated on both natural and man-made objects. It is a good human-computer interaction practice which draws from supporting knowledge on both the machine side and the human side.

Keywords: 3d printing, perceptual model, fuzzy evaluation, data-driven approach

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715 SCNet: A Vehicle Color Classification Network Based on Spatial Cluster Loss and Channel Attention Mechanism

Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

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Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

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714 Agile Methodology for Modeling and Design of Data Warehouses -AM4DW-

Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

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713 The Effect of Combined Doxorubicin and Dioscorea esculenta on Apoptosis Induction in Human Breast Cancer Cells

Authors: Dina Fatmawati, Sofia Mubarika, Mae Sri Wahyuningsih

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Chemotherapy for breast cancer is largely ineffective, but innovative combinations of chemotherapeutic agents and natural compounds represent a promising strategy. In our previous study, the combination of Doxorubicin (Dox) and ethanolic extract of Dioscorea esculenta tuber ((EED) was found to have a synergistic effect on T47D human breast cancer cell line. In this study, we investigated the apoptotic effect of the combination on T47D human breast cancer cells and normal fibroblasts cell line and its effects on the expression of Caspase-3 and cleaved poly (ADP-Ribose) Polymerase-1 (cPARP-1) protein. T47D cell lines and fibroblasts cells were treated with the combination of Dox and EED. Apoptotic effect of the combination was determined using flow cytrometry assay. Protein expressions were determined by immunocytochemistry staining. The percentage of apoptotic cells were significantly higher in T47D cell lines (75%) than that of in fibroblast cells (23%). The expression of Caspase 3 (84.53%) and cPARP-1 (83.36%) were significantly higher in the cancer cell lines than those of normal cells. These results indicate that the combination of doxorubicin and Dioscorea esculenta is a promising candidate for the treatment of breast cancer cells.

Keywords: Dioscorea esculenta, Doxorubicin, apoptosis, immunocytochemistry, cancer cells

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712 Morphological Differentiation and Temporal Variability in Essential Oil Yield and Composition among Origanum vulgare ssp. hirtum L., Origanum onites L. and Origanum x intercedens from Ikaria Island (Greece)

Authors: A.Assariotakis, P. Vahamidis, P. Tarantilis, G. Economou

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Greece, due to its geographical location and the particular climatic conditions, presents high biodiversity of Medicinal and Aromatic Plants. Among them, the genus Origanum not only presents a wide distribution, but it also has great economic importance. After extensive surveys in Ikaria Island (Greece), 3 species of the genus Origanum were identified, namely, Origanum vulgare ssp. hirtum (Greek oregano), Origanum onites (Turkish oregano) and Origanum x intercedens (hybrid), a naturally occurring hybrid between O. hirtum and O. onites. The purpose of this study was to determine their morphological as well as their temporal variability in essential oil yield and composition under field conditions. For this reason, a plantation of each species was created using vegetative propagation and was established at the experimental field of the Agricultural University of Athens (A.U.A.). From the establishment year and for the following two years (3 years of observations), several observations were taken during each growing season with the purpose of identifying the morphological differences among the studied species. Each year collected plant (at bloom stage) material was air-dried at room temperature in the shade. The essential oil content was determined by hydrodistillation using a Clevenger-type apparatus. The chemical composition of essential oils was investigated by Gas Chromatography-Mass Spectrometry (GC – MS). Significant differences were observed among the three oregano species in terms of plant height, leaf size, inflorescence features, as well as concerning their biological cycle. O. intercedens inflorescence presented more similarities with O. hirtum than with O. onites. It was found that calyx morphology could serve as a clear distinction feature between O. intercedens and O. hirtum. The calyx in O. hirtum presents five isometric teeth whereas in O. intercedens two high and three shorter. Essential oil content was significantly affected by genotype and year. O. hirtum presented higher essential oil content than the other two species during the first year of cultivation, however during the second year the hybrid (O. intercedens) recorded the highest values. Carvacrol, p-cymene and γ-terpinene were the main essential oil constituents of the three studied species. In O. hirtum carvacrol content varied from 84,28 - 93,35%, in O. onites from 86,97 - 91,89%, whereas in O. intercedens it was recorded the highest carvacrol content, namely from 89,25 - 97,23%.

Keywords: variability, oregano biotypes, essential oil, carvacrol

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711 Genetic Improvement Potential for Wood Production in Melaleuca cajuputi

Authors: Hong Nguyen Thi Hai, Ryota Konda, Dat Kieu Tuan, Cao Tran Thanh, Khang Phung Van, Hau Tran Tin, Harry Wu

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Melaleuca cajuputi is a moderately fast-growing species and considered as a multi-purpose tree as it provides fuelwood, piles and frame poles in construction, leaf essential oil and honey. It occurs in Australia, Papua New Guinea, and South-East Asia. M. cajuputi plantation can be harvested on 6-7 year rotations for wood products. Its timber can also be used for pulp and paper, fiber and particle board, producing quality charcoal and potentially sawn timber. However, most reported M. cajuputi breeding programs have been focused on oil production rather than wood production. In this study, breeding program of M. cajuputi aimed to improve wood production was examined by estimating genetic parameters for growth (tree height, diameter at breast height (DBH), and volume), stem form, stiffness (modulus of elasticity (MOE)), bark thickness and bark ratio in a half-sib family progeny trial including 80 families in the Mekong Delta of Vietnam. MOE is one of the key wood properties of interest to the wood industry. Non-destructive wood stiffness was measured indirectly by acoustic velocity using FAKOPP Microsecond Timer and especially unaffected by bark mass. Narrow-sense heritability for the seven traits ranged from 0.13 to 0.27 at age 7 years. MOE and stem form had positive genetic correlations with growth while the negative correlation between bark ratio and growth was also favorable. Breeding for simultaneous improvement of multiple traits, faster growth with higher MOE and reduction of bark ratio should be possible in M. cajuputi. Index selection based on volume and MOE showed genetic gains of 31 % in volume, 6 % in MOE and 13 % in stem form. In addition, heritability and age-age genetic correlations for growth traits increased with time and optimal early selection age for growth of M. cajuputi based on DBH alone was 4 years. Selected thinning resulted in an increase of heritability due to considerable reduction of phenotypic variation but little effect on genetic variation.

Keywords: acoustic velocity, age-age correlation, bark thickness, heritability, Melaleuca cajuputi, stiffness, thinning effect

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710 Feasibility of Chicken Feather Waste as a Renewable Resource for Textile Dyeing Processes

Authors: Belayihun Missaw

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Cotton cationization is an emerging area that solves the environmental problems associated with the reactive dyeing of cotton. In this study, keratin hydrolysate cationizing agent from chicken feather was extracted and optimized to eliminate the usage of salt during dyeing. Cationization of cotton using the extracted keratin hydrolysate and dyeing of the cationized cotton without salt was made. The effect of extraction parametric conditions like concentration of caustic soda, temperature and time were studied on the yield of protein from chicken feather and colour strength (K/S) values, and these process conditions were optimized. The optimum extraction conditions were. 25g/l caustic soda, at 500C temperature and 105 minutes with average yield = 91.2% and 4.32 colour strength value. The effect of salt addition, pH and concentration of cationizing agent on yield colour strength was also studied and optimized. It was observed that slightly acidic condition with 4% (% owf) concentration of cationizing agent gives a better dyeability as compared to normal cotton reactive dyeing. The physical properties of cationized-dyed fabric were assessed, and the result reveals that the cationization has a similar effect as normal dyeing of cotton. The cationization of cotton with keratin extract was found to be successful and economically viable.

Keywords: cotton materials, cationization, reactive dye, keratin hydrolysate

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709 Anticancer Activity of Edible Coprinus Mushroom (Coprinus comatus) on Human Glioblastoma Cell Lines and Interaction with Temozolomide

Authors: Maria Borawska, Patryk Nowakowski, Sylwia K. Naliwajko, Renata Markiewicz-Zukowska, Anna Puscion-Jakubik, Krystyna Gromkowska-Kepka, Justyna Moskwa

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Coprinus comatus (O. F. Müll.) Pers.) should not be confused with the common Ink Cap, which contains coprine and can induce coprine poisoning. We study the possibility of applying coprinus mushroom (Coprinus comatus), available in Poland, as food product supporting the treatment of human glioblastoma cells. The U87MG and T98 glioblastoma cell lines were exposed to water (CW) or ethanol 95° (CE) Cantharellus extracts (50-500 μg/ml), with or without temozolomide (TMZ) during 24, 48 or 72 hours. The cell division was examined by the H³-thymidine incorporation. The statistical analysis was performed using Statistica v. 13.0 software. Significant differences were assumed for p < 0.05. We found that both, CW and CE, administrated alone, had inhibitory effect on cell lines growth, but the CE extract had a higher degree of growth inhibition. The anti-tumor effect of TMZ (50 μM) on U87MG was enhanced by mushroom extracts, and the effect was lower to the effect after using Coprinus comatus extracts (CW and CE) alone. A significant decrease (p < 0.05) in pro-MMP2 (82.61 ± 6.3% of control) secretion in U87MG cells was observed after treated with CE (250 μg/ml). We conclude that extracts of Coprinus comatus, edible mushroom, present cytotoxic properties on U87MG and T98 cell lines and may cooperate with TMZ synergistically enhancing its growth inhibiting activity against glioblastoma U87MG cell line.

Keywords: anticancer, glioma, mushroom, temozolomide

Procedia PDF Downloads 173