Search results for: vetiver root extract

Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe

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Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.

Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects

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Authors: Zahra Mohagheghian, Fatema Agharebparast

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Professional ethic is a subject that has been an issue today, so most of the businesses, including the teaching profession, understand the need and importance of it. So they need to develop a code of professional ethics for their own. In this regard, this study seeks to answer the question, with respect to the integrity of the Qur'an (Nahl / 89), is it possible to contemplate the divine teachers conduct to extract the divine pattern for teaching and training? In the code of conduct for divine teachers what are the most important moral obligations and duties of the teaching professionals? The results of this study show that the teaching of Khidr, according to the Quran’s verses, Abundant and subtle hints emphasized that it can be as comprehensive and divine pattern used in teaching and in the drafting of the charter of professional ethics of teachers used it. Also, the results show that in there have been many ethical principles in prophet Khidr’s teaching pattern.The most important ethical principles include: Student assessment, using objective and not subjective examples, assessment during teaching, flexibility, and others. According to each of these principles can help teachers achieve their educational goals and lead human being in their path toward spiritual evaluation.

Keywords: professional ethics, teaching-learning process, teacher, student, Quran

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Authors: N. Drir, L. Barazane, M. Loudini

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It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.

Keywords: maximum power point tracking, neural networks, photovoltaic, P&O

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Authors: Rula D. Alshareef, Safa S. Alqathmi, Ghadah K. Alkhouldi, Reem O. Bagabas, Farheen B. Hasan

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Safety engineering is among the most crucial considerations in any work environment. Providing mentally, physically, and environmentally safe work conditions must be the top priority of any successful organization. Company X is a local paint production company in Saudi Arabia; in a month, the factory experienced two significant accidents, which indicates that workers’ safety is overlooked. The aim of the research is to examine the risks, assess the root causes and recommend control measures that will eventually contribute to providing a safe workplace. The methodology used is sectioned into three phases, risk identification, assessment, and finally, mitigation. In the identification phase, the team used Rapid Entire Body Assessment (REBA) and National Institute for Occupational Safety and Health Lifting Index (NIOSH LI) tools to holistically establish knowledge about the current risk posed to the factory. The physical hazards in the factory were assessed in two different operations, which are mixing and filling/packaging. For the risk assessment phase, the hazards were deeply analyzed through their severity and impact. Additionally, through risk mitigation, the Rapid Entire Body Assessment (REBA) score decreased from 11 to 7, and the National Institute for Occupational Safety and Health Lifting Index (NIOSH LI) has been reduced from 5.27 to 1.85.

Keywords: ergonomics, safety, workplace risks, hazards, awkward posture, fatigue, work environment

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Authors: Khater N., Rahmine S., Bougoffa C., Bouguenna T., Ouanes H.

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Moringa oleifera L. species is considered one of the most useful trees in the world, possessing many interesting properties that make it of great scientific interest. It has been described as the miracle tree, the tree of a thousand virtues, the tree of life and God's gift to man. The present study aims to introduce, produce, and develop Moringa Oleifera as a species with high ecological potential (resistance to biotic and abiotic stresses and productivity), high added value, and multiple virtues. The aim of this work is to study the germination potential of this species under different temperature conditions. In this study, the germination assay was tested in two different temperature ranges: internal (laboratory ambient temperature between 22°c and 25°c) and external (seasonal temperature between 4°c and 8°c). Morphological and physiological analyses were carried out by Shoot length (SL), root length (RL), diameter at the crown (DC), fresh weight of shoots (FWS), fresh weight of roots (FWR), dry weight of shoots (DWS) and dry weight of roots (DWS). For all these variables, the results of the study reveal a significant difference between the two temperature intervals, with a high germination rate of 81. 81% and plant growth was rapid (7cm during 24h) in the laboratory temperature; in contrast to the external temperatures, a germination rate value of around 27% was recorded, and germination took place after 20 days of sowing, with slower plant growth. The results obtained show that a temperature greater than or equal to 25° is the ideal temperature for the germination and growth of moringa seeds and has a positive influence on the speed and percentage of germination.

Keywords: moringa oleifera, temperature, germination rate, growth, biomass

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Authors: Maram Saleh

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Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

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Authors: Feng Yang

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Machine learning (ML), especially deep learning (DL), has been extensively applied to many applications in recently years and gained great success in solving different problems, including scientific problems. However, conventional ML/DL methodologies are purely data-driven which have the limitations, such as need of ample amount of labelled training data, lack of consistency to physical principles, and lack of generalizability to new problems/domains. Recently, there is a growing consensus that ML models need to further take advantage of prior knowledge to deal with these limitations. Physics-informed machine learning, aiming at integration of physics/domain knowledge into ML, has been recognized as an emerging area of research, especially in the recent 2 to 3 years. In this work, physics-informed ML, specifically physics-informed neural network (NN), is employed and implemented to estimate the displacements at x, y, z directions in a solid mechanics problem that is controlled by equilibrium equations with boundary conditions. By incorporating the physics (i.e. the equilibrium equations) into the learning process of NN, it is showed that the NN can be trained very efficiently with a small set of labelled training data. Experiments with different settings of the NN model and the amount of labelled training data were conducted, and the results show that very high accuracy can be achieved in fulfilling the equilibrium equations as well as in predicting the displacements, e.g. in setting the overall displacement of 0.1, a root mean square error (RMSE) of 2.09 × 10−4 was achieved.

Keywords: deep learning, neural network, physics-informed machine learning, solid mechanics

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Authors: Imran Ullah Imran

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Language contact is a familiar concept in the present global world. Across the globe, languages get mixed up at different levels. Borrowing, code-switching are some of the means through which languages interact. This study examines Pashto-English contact at word and syllable levels. By recording the speech of 30 Pashto native speakers, selected via 'social network' sampling, the study located a number of Pashto-English compound words, which is a unique contact of its kind. In data analysis, tokens were categorized on the basis of their pattern and morphological structure. The study shows that Pashto-English Bilingual Compound words (BCWs) are very prevalent in the Pashto language. The study also found that the BCWs in Pashto are completely productive and have their own meanings. It also shows that the dominant pattern of hybrid words in Pashto is the conjugation of an independent English root word followed by a Pashto inflectional morpheme, which contributes to the core semantic content of the construction. The BCWs construction shows that how both the languages are closer to each other. Pashto-English contact results into bilingual compound and hybrid words, which forms a considerable number of tokens in the present-day spoken Pashto. On the basis of these findings, the study assumes that the same phenomenon may increase with the passage of time that would, in turn, result in the formation of more bilingual compound or hybrid words.

Keywords: code-mixing, bilingual compound words, pashto-english contact, hybrid words, inflectional lexical morpheme

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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Authors: Arash Jafari, Somaye Bahrami, Mohammad Hossein Razi Jalali

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The aim of this study was the isolation and identification of excretory-secretory and somatic antigens from D. dendriticum by SDS-PAGE and evaluation of humeral immune response against these antigens. The sera of infected sheep with different infection degrees were collected. Somatic and ES proteins were isolated with SDS PAGE. Immunogenicity properties of the resulting proteins were determined using western blot analysis. The total extract of somatic antigens analysed by SDS-PAGE revealed 21 proteins. In mild infection, bands of 130 KDa were immune dominant. In moderate infections 48, 80 and 130 KDa and in heavy infections 48, 60, 80, 130 KDa were detected as immune dominant bands. In ES antigens, mild infection 130 KDa, in moderate infection 100, 120 and 130 KDa and in heavy infection 45, 80, 85, 100, 120 and 130 KDa were immune dominant bands. The most immunogenic protein band during different degrees of infection was 130KDa.

Keywords: Dicrocoelium dendriticum excretory-secretory antigens, somatic antigens, western blot

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Authors: Doni Dermawan

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Hypertension is a disease with a high prevalence in Indonesia. The prevalence of hypertension in Indonesia is based on the Basic Health Research (Riskesdas) in 2013 which amounted to 25.8%. Medicinal plants have been widely used to treat hypertension including roselle (Hibiscus sabdariffa L.) and garlic (Allium sativum L.) by a mechanism as angiotensin converting enzyme (ACE) inhibitor. The purpose of this research is to analyze the in silico (molecular studies) of pharmacological effects and toxicity of roselle (Hibiscus sabdariffa L.) and garlic (Allium sativum L.) as well as a combination of both are used as antihypertensive herbs. The results of study showed that roselle (Hibiscus sabdariffa L.) and garlic (Allium sativum L.) have great potential as antihypertensive herbs based on the affinity and stability of active substances to specific receptor with a much better value than a of antihypertensive drugs (lisinopril). Toxicity values determined by the method of AST, ALT and ALP in which the three values obtained indicate the presence of acute toxic effects that need to be considered in determining the dose of the extract of roselle and garlic as antihypertensives.

Keywords: Allium sativum, antihypertensive, Hibiscus sabdariffa, in silico, toxicity

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Authors: Gubiani Rino, Nicola Zucchiatti, Da Broi Ugo, Bietresato Marco

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The problem of vibrations in agriculture is very important due to the different types of machinery used for the different types of soil in which work is carried out. One of the most commonly used machines is the tractor, where the phenomenon has been studied for a long time by measuring the whole body and placing the sensor on the seat. However, this measurement system does not take into account the characteristics of the drivers, such as their body index (BMI), their gender (male, female) or the muscle fatigue they are subjected to, which is highly dependent on their age for example. The aim of the research was therefore to place sensors not only on the seat but along the spinal column to check the transmission of vibration on drivers with different BMI on different tractors and at different travel speeds and of different genders. The test was also done using wearable sensors such as a dynamometer applied to the muscles, the data of which was correlated with the vibrations produced by the tractor. Initial data show that even on new tractors with pneumatic seats, the vibrations attenuate little and are still correlated with the roughness of the track travelled and the forward speed. Another important piece of data are the root-mean square values referred to 8 hours (A(8)x,y,z) and the maximum transient vibration values (MTVVx,y,z) and, the latter, the MTVVz values were problematic (limiting factor in most cases) and always aggravated by the speed. The MTVVx values can be lowered by having a tyre-pressure adjustment system, able to properly adjust the tire pressure according to the specific situation (ground, speed) in which a tractor is operating.

Keywords: fatigue, effect vibration on health, tractor driver vibrations, vibration, muscle skeleton disorders

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Authors: S. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

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One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: spoken dialog system, spoken language understanding, web semantic, name entity recognition

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Authors: Saifullah K., Muhammad Naziruddin Saifullah, Muhammad N.

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The bio control potential and mechanism of P. chlamydosporia against Meloidogyne incognita was evaluated in the present study. Under invitro conditions, P. chlamydosporia was tested for parasitism of eggs and females of M. incognita. The results indicated that this fungus parasitized 87% eggs and 82% females. Culture filtrate (CF) of P. chlamydosporia was tested for its larvicide activity against M. incognita 2nd stage juvenile. The maximum mortality was 97.3% at 100% concentration of the culture filtrate while minimum mortality was 7.3% in 25% concentration after 24 hrs. The result of the pot experiment proved that P. chlamydosporia has reduced the incidence of RKN and improved all tested agronomic growth parameters. The treatment with inoculated M. incognita alone reduced plant height, fresh shoot, and fresh root weight by 44.7%, 29.8%, and 32.8% respectively over uninoculated healthy control. Histopathological studies on the interaction of Pochonia chlamydosporia and Meloidogyne incognita on tomato roots revealed anatomical changes among treatments. Less number of galls with small in size and scarcer abnormalities in the vascular cylinder was observed in plants inoculated with P. chlamydosporia and M. incognita than the plants treated with nematode only. The fungus was seen in in the intercellular spaces of cortical and epidermal cells while the vascular bundles of the plant remain intact, inoculated only with P. chlamydosporia. In the infected roots, many mature females were seen which feed on giant cells. The findings also revealed that control healthy plants were not affected and no histological changes were noted.

Keywords: histopathology, Pochonia chlamydosporia, Meloidogyne incognita, tomato

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Authors: Anika Pallapothu

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Periodontitis, a severe gum disease, poses a significant threat to the integrity of bone and soft tissues supporting teeth, primarily initiated by bacterial accumulation around the gum line. Conventional treatments like scaling/root planning and plaque removal are widely employed, but integrating modern technologies such as nanotechnology holds promise for innovative therapeutic approaches. This study explores the utilization of silver nanoparticles encapsulated within cellulose nanofiber (CNF) and mesoporous bioactive glass hydrogel matrices for periodontitis management. Silver nanoparticles exhibit potent antimicrobial properties by disrupting microbial cell membranes, inducing reactive oxygen species (ROS) generation, and interfering with vital cellular processes like ATP production and nucleic acid synthesis. Mesoporous bioactive glass, renowned for its high surface area, osteoconductive, and bioactivity, presents a favorable platform for pharmaceutical applications. Incorporating CNF enhances the properties of the hydrogel due to its biocompatibility, biodegradability, and water absorption capacity. The proposed composite material is anticipated to exert beneficial effects in periodontitis treatment by demonstrating antibacterial and anti-inflammatory activities, offering a promising avenue for future therapeutic interventions.

Keywords: periodontitis, cellulose nanofibers, silver nanoparticles, mesoporous bioactive glass, antibacterial activity, anti-inflammatory activity

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Authors: Samiah Rehman, Kashmira J. Gohil

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Objective: Dracaena trifascaita extract (DTE) possesses strong antioxidant and anti-inflammatory properties that play a vital role in the treatment of mental disorders like depression. The present study was designed to evaluate the antidepressant effects of hydroalcoholic extracts of DT on behavioral models of depression. Methodology: Animals were randomly divided into 6 groups of 5 each: Group 1 and 2 received distilled water and standard drug, imipramine: 25mg/kg, respectively. Groups 4, 5 and 6 received DTE treatment orally at doses of 200 ,400 and 600mg/ kg, respectively, for 14 days. Time of immobility was noted by force swimming test (FST)and tail suspension test (TST) on the 1st,7th and 14th days. Results: The time of immobility was reduced in the treatment group as compared to the control and standard. DTE600 mg/kg showed the highest and most significant antidepressant effects as compared to the standard drug imipramine. (25mg/kg). Conclusion: DTE has good potential as an alternative therapy for depression.

Keywords: Dracaena trifasciata, antidepressants, force swimming test, tail suspension test, herbal drug of depression

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Authors: Mehdi Nasr-Esfahani, Leila Mohammad Bagheri, Ava Nasr-Esfahani

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Root and collar rot disease caused by Phytophthora capsici (Leonian) is one of the most serious diseases in pepper, Capsicum annuum L. In this study, a diverse collection of 37 commercial edible and ornamental pepper genotypes infected with P. capsici were investigated for biomass parameters and enzymatic activity of peroxidase or peroxide reductases (EC), superoxide dismutase (SOD), polyphenol oxidase (PPOs), catalase (CAT) and phenylalanine ammonia-lyase (PAL). Seven candidate DEG genes were also evaluated on resistant and susceptible pepper cultivars, through measuring product formation, using spectrophotometry and real-time polymerase chain reaction. All the five enzymes and seven defense-gene candidates were up-regulated in all inoculated pepper accessions to P. capsici. But, the enzymes and DEG genes were highly expressed in resistant cv. 19OrnP-PBI, 37ChillP-Paleo, and “23CherryP-Orsh". The expression level of enzymes were 1.5 to 5.6-fold higher in the resistant peppers, than the control non-inoculated genotypes. Also, the transcriptional levels of related candidate DEG genes were 3.16 to 5.90-fold higher in the resistant genotypes. There was a direct and high correlation coefficient between resistance, bio-mass parameters, enzymatic activity, and resistance gene expression. The related enzymes and candidate genes expressed herein will provide a basis for further gene cloning and functional verification studies, and also will aid in an understanding of the regulatory mechanism of pepper resistance to P. capsici.

Keywords: AP2/ERF, cDNA, enzymes, MIP gene, q-RTPCR, XLOC

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Authors: Rini Jarial, Puranjan Mishra, Lakhveer Singh, Sveta Thakur, A. W. Zularisam, Mimi Sakinah

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The aim of the present study was to assess the biological properties of Camellia sinensis and to identify its functional compounds. The methanolic leaves-extract (MLE) of commercial green tea (Camellia sinensis) was assessed for anti-bacterial activities by measuring inhibition zones against a panel of pathogenic bacterial strains using agar diffusion method. The flavonoid (5.0 to 8.0 mg/ml) and protein content (10 to 15 mg/ml) of the MLE were recorded. MLE at a concentration of 25 μg/ml showed marked anti-bacterial activity against all bacterial strains (11-30 mm zone of inhibition) and was maximum against Staphylococcus aureus (30 mm). The MLE of Camellia sinensis had the best MIC values of 2.25 and 0.56 mg/ml against S. aureus and Enterobacter sp., respectively. The MLE also possessed good anti-lipolytic activity (65%) against a Porcine pancreatic lipase (PPL) and cholesterol oxidase inhibition (79%). The present study provided strong experimental evidences that the MLE of Camellia sinensis is not only a potent source of natural anti-oxidants and anti-bacterial activity but also possesses efficient cholesterol degradation and anti-lipolytic activities that might be beneficial in the body weight management.

Keywords: anti-oxidant, anti-bacterial activity, anti-lipolytic activity, Camellia sinensis, phyto-chemicals

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Authors: Khamael M. Abualnaja, Lidija Šiller, Benjamin R. Horrocks

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Alkylated silicon nanocrystals (C11-SiNCs) were prepared successfully by galvanostatic etching of p-Si(100) wafers followed by a thermal hydrosilation reaction of 1-undecene in refluxing toluene in order to extract C11-SiNCs from porous silicon. Erbium trichloride was added to alkylated SiNCs using a simple mixing chemical route. To the best of our knowledge, this is the first investigation on mixing SiNCs with erbium ions (III) by this chemical method. The chemical characterization of C11-SiNCs and their mixtures with Er3+ (Er/C11-SiNCs) were carried out using X-ray photoemission spectroscopy (XPS). The optical properties of C11-SiNCs and their mixtures with Er3+ were investigated using Raman spectroscopy and photoluminescence (PL). The erbium-mixed alkylated SiNCs shows an orange PL emission peak at around 595 nm that originates from radiative recombination of Si. Er/C11-SiNCs mixture also exhibits a weak PL emission peak at 1536 nm that originates from the intra-4f transition in erbium ions (Er3+). The PL peak of Si in Er/C11-SiNCs mixture is increased in the intensity up to three times as compared to pure C11-SiNCs. The collected data suggest that this chemical mixing route leads instead to a transfer of energy from erbium ions to alkylated SiNCs.

Keywords: photoluminescence, silicon nanocrystals, erbium, Raman spectroscopy

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Authors: H. Kadi, A. Moussaoui, A. Medah, N. Benayahia, Nahal Bouderba

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For thousands of years, Punica granatum L. has been used in traditional medicine all over the world and predate the introduction of antibacterial drugs. The aim of the present study was to investigate the antibacterial activity of aqueous and ethanolic extracts of Punica granatum L. bark obtained by decoction and maceration. The different extracts of Punica granatum L. (Lythraceae) bark have been tested for antibacterial activity against Gram-positive bacteria (Staphylococcus aureus, Bacillus stearothermophilus) and Gram-negative bacteria (Escherichia coli, Pseudomonas aeruginosa) by disc diffusion method. The ethanolic macerate extract showed the strong in vitro antibacterial activity against Pseudomonas aeruginosa with zone inhibition of 24.4 mm. However, the results tests by disc diffusion method revealed the effectiveness of ethanolic decoctate against Gram-positive bacteria (Staphylococcus aureus and Bacillus stearothermophilus) with diameter zone of inhibition varying with 21.1mm and 23.75 mm respectively.

Keywords: Punica granatum L. bark, antibacterial activity, maceration, decoction

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Authors: Zia Ullah, Muhammad Asim, Shi Sujuan, Rayyan Khan, Aaqib Shaheen, LIU Haobao

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The plant-specific auxin efflux proteins PIN-FORMED (PIN) have been well depicted in many plant species for their essential roles in regulating the transport of auxins in several phases of plant growth. Little is known about the various functions of the PIN family genes in the Nicotiana tabacum (N. tabacum) species during plant growth. To define the expression pattern of the NtPIN1a gene under abiotic stresses and hormone treatment, transgenic tobacco with promoterNtPIN1a::GUS construct was employed. Comprehensive computational analyses of the NtPIN1a promoter confirmed the existence of common core promoter elements including CAAT-box, TATA-box, hormone, and abiotic stress-responsive elements such as ABRE, P-box, MYC, MYB, ARE, and GC-motifs. The transgenic plants with the promoter of NtPIN1a displayed a promising expression of β-glucuronidase (GUS) in germinating seeds, root tips, shoot-apex, and developing leaves under optimal conditions. While the differential expression of GUS in moderate salt, drought, low potassium stresses, and externally high auxin level at two different time points, suggested NtPIN1a played a key role in growth processes and the plants’ response to abiotic stresses. This analysis provides a foundation for more in-depth discoveries of the biological functions of NtPIN1a in Nicotiana species and this promoter may be employed in genetic engineering of other crops for enhanced stress tolerance.

Keywords: tobacco, nicotiana tabacum, pin, promoter, GUS, abiotic stresses, auxin

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Authors: Enva Doda

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Recent statistical analyses within the European Union (EU) underscore the enduring significance of the Gender Pay Gap in amplifying the Gender Pension Gap, a phenomenon resisting proportional reduction over time. This study meticulously calculates the Pension Gap, scrutinizing contributing variables within diverse pension systems. Furthermore, it investigates whether the "unexplained" segment of the Gender Gap correlates with political institutions, economic systems, historical events, or discrimination, utilizing quantitative methods and the Blinder-Oaxaca Decomposition Method to pinpoint potential discriminatory factors. The descriptive analysis reveals a conspicuous Gender Pension Gap across European nations, displaying notable variation. While an overall reduction in the Gender Gap is observed, the degree of improvement varies among countries. Subsequent analyses will delve into the specific reasons or variables influencing distinct Gender Gap percentages, forming the basis for nuanced policy recommendations. This comprehensive research enriches the ongoing discourse on gender equality and economic equity. By focusing on the root causes of the Pension Gap, the study has the potential to instigate policy adjustments, urging policymakers to reassess systemic structures and contribute to informed decision-making. Emphasizing gender equality as essential for a flourishing and resilient economy, the research aspires to drive positive change on academic and policy fronts.

Keywords: blinder Oaxaca decomposition method, discrimination, gender pension gap, quantitative methods, unexplained gender gap

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Authors: Shahrokh Ranjbar-Bahadori, Nima Farhadifar, Leila Mohammadyar

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Plant preparations from thyme and garlic have been shown to be effective acaricides against the poultry red mite, Dermanyssus gallinae. In a layer house with a history of D. gallinae problem, mites were detected in the monitoring traps for the first time and number of them was counted. Then, some rows of layer house was sprayed twice using a concentration of 0.21 mg/cm2 thyme essential oil and 0.07 mg/cm2 garlic juice and a similar row was used as an untreated control group. Red mite traps made of cardboard were used to assess the mite density during days 1 and 7 after treatment and always removed after 24 h. the collected mites were counted and the efficacy against all mite stages (larvae, nymphs and adults) was calculated. Results showed that on day 1 and 7 after the administration of garlic extract efficacy rate was 92.05% and 74.62%, respectively. Moreover, efficacy rate on day 1 and 7 was 89.4% and 95.37% when treatment was done with thyme essential oil. It is concluded that using garlic juice to control of D. gallinae is more effective on short time. But thyme essential oil has a long time effect in compare to garlic preparation.

Keywords: Dermanyssus gallinae, essential oil, garlic, thyme, efficacy

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Authors: Mukesh Singh Boori, Vít Voženílek

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Olomouc is a unique and complex landmark with widespread forestation and land use. This research work was conducted to assess important and complex land use change trajectories in Olomouc region. Multi-temporal satellite data from 1991, 2001 and 2013 were used to extract land use/cover types by object oriented classification method. To achieve the objectives, three different aspects were used: (1) Calculate the quantity of each transition; (2) Allocate location based landscape pattern (3) Compare land use/cover evaluation procedure. Land cover change trajectories shows that 16.69% agriculture, 54.33% forest and 21.98% other areas (settlement, pasture and water-body) were stable in all three decade. Approximately 30% of the study area maintained as a same land cove type from 1991 to 2013. Here broad scale of political and socio-economic factors was also affect the rate and direction of landscape changes. Distance from the settlements was the most important predictor of land cover change trajectories. This showed that most of landscape trajectories were caused by socio-economic activities and mainly led to virtuous change on the ecological environment.

Keywords: remote sensing, land use/cover, change trajectories, image classification

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Authors: Fatma Abdedayem

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We propose an extension to the famous method called Bag of words (BOW) which proved a successful role in the field of image categorization. Practically, this method based on representing image with visual words. In this work, firstly, we extract features from images using Spatial Pyramid Representation (SPR) and two dissimilar color descriptors which are opponent-SIFT and transformed-color-SIFT. Secondly, we fuse color local features by joining the two histograms coming from these descriptors. Thirdly, after collecting of all features, we generate multi-dictionaries coming from n random feature subsets that obtained by dividing all features into n random groups. Then, by using these dictionaries separately each image can be represented by n histograms which are lately concatenated horizontally and form the final histogram, that allows to combine Multiple Dictionaries (MDBoW). In the final step, in order to classify image we have applied Support Vector Machine (SVM) on the generated histograms. Experimentally, we have used two dissimilar image datasets in order to test our proposition: Caltech 256 and PASCAL VOC 2007.

Keywords: bag of words (BOW), color descriptors, multi-dictionaries, MDBoW

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Authors: G. Blázquez, A. Gálvez-Pérez, M. Calero, I. Iáñez-Rodríguez, M. A. Martín-Lara, A. Pérez

Abstract:

The production of olive oil is considered as one of the most important agri-food industries. However, some of the by-products generated in the process are potential pollutants and cause environmental problems. Consequently, the management of these by-products is currently considered as a challenge for the olive oil industry. In this context, several technologies have been developed and tested. In this sense, the autohydrolysis of these by-products could be considered as a promising technique. Therefore, this study focused on autohydrolysis treatments of a solid residue from the olive oil industry denominated olive cake. This one comes from the olive pomace extraction with hexane. Firstly, a water washing was carried out to eliminate the water soluble compounds. Then, an experimental design was developed for the autohydrolysis experiments carried out in the hydrothermal pressure reactor. The studied variables were temperature (30, 60 and 90 ºC) and time (30, 60, 90 min). On the other hand, aliquots of liquid obtained fractions were analysed by HPLC to determine the fructose and sucrose contents present in the liquid fraction. Finally, the obtained results of sugars contents and the yields of the different experiments were fitted to a neuro-fuzzy and to a polynomial model.

Keywords: ANFIS, olive cake, polyols, saccharides

Procedia PDF Downloads 155

Authors: Dipali Nagaonkar, Mahendra Rai

Abstract:

Chitosan, a carbohydrate polymer at nanoscale level has gained considerable momentum in drug delivery applications due to its inherent biocompatibility and non-toxicity. However, conventional synthetic strategies for chitosan nanoparticles mainly rely upon physicochemical techniques, which often yield chitosan microparticles. Hence, there is an emergent need for development of controlled synthetic protocols for chitosan nanoparticles within the nanometer range. In this context, we report the green synthesis of size controlled chitosan nanoparticles by using Pongamia pinnata (L.) leaf extract. Nanoparticle tracking analysis confirmed formation of nanoparticles with mean particle size of 85 nm. The stability of chitosan nanoparticles was investigated by zetasizer analysis, which revealed positive surface charged nanoparticles with zeta potential 20.1 mV. The green synthesized chitosan nanoparticles were further explored for encapsulation and controlled release of antioxidant biomolecule, quercetin. The resulting drug loaded chitosan nanoparticles showed drug entrapment efficiency of 93.50% with drug-loading capacity of 42.44%. The cumulative in vitro drug release up to 15 hrs was achieved suggesting towards efficacy of green synthesized chitosan nanoparticles for drug delivery applications.

Keywords: Chitosan nanoparticles, green synthesis, Pongamia pinnata, quercetin

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Authors: Andre Peres Ramos, Franklin Cesar Flores

Abstract:

Colorization is the process of add colors to a monochromatic image or video. Usually, the process involves to segment the image in regions of interest and then apply colors to each one, for videos, this process is repeated for each frame, which makes it a tedious and time-consuming job. We propose a new assisted method for video colorization; the user only has to colorize one frame, and then the colors are propagated to following frames. The user can intervene at any time to correct eventual errors in color assignment. The method consists of to extract intensity and texture descriptors from the frames and then perform a feature matching to determine the best color for each segment. To reduce computation time and give a better spatial coherence we narrow the area of search and give weights for each feature to emphasize texture descriptors. To give a more natural result, we use an optimization algorithm to make the color propagation. Experimental results in several image sequences, compared to others existing methods, demonstrates that the proposed method perform a better colorization with less time and user interference.

Keywords: colorization, feature matching, texture descriptors, video segmentation

Procedia PDF Downloads 162

Authors: Akinbo Razak Yinka, Adesanya Kehinde Kazeem, Oladokun Oluwagbenga Peter

Abstract:

Time series data are sequences of observations collected over a period of time. Such data can be used to predict health outcomes, such as disease progression, mortality, hospitalization, etc. The Statistical approach is based on mathematical models that capture the patterns and trends of the data, such as autocorrelation, seasonality, and noise, while Neural methods are based on artificial neural networks, which are computational models that mimic the structure and function of biological neurons. This paper compared both parametric and non-parametric time series models of patients treated for malaria in Maternal and Child Health Centres in Lagos State, Nigeria. The forecast methods considered linear regression, Integrated Moving Average, ARIMA and SARIMA Modeling for the parametric approach, while Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) Network were used for the non-parametric model. The performance of each method is evaluated using the Mean Absolute Error (MAE), R-squared (R2) and Root Mean Square Error (RMSE) as criteria to determine the accuracy of each model. The study revealed that the best performance in terms of error was found in MLP, followed by the LSTM and ARIMA models. In addition, the Bootstrap Aggregating technique was used to make robust forecasts when there are uncertainties in the data.

Keywords: ARIMA, bootstrap aggregation, MLP, LSTM, SARIMA, time-series analysis

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Authors: Kamal Amarouche, Houda Benbrahim, Ismail Kassou

Abstract:

Nowadays, e-commerce shopping websites have experienced noticeable growth. These websites have gained consumers’ trust. After purchasing a product, many consumers share comments where opinions are usually embedded about the given product. Research on the automatic management of opinions that gives suggestions to potential consumers and portrays an image of the product to manufactures has been growing recently. After launching the product in the market, the reviews generated around it do not usually contain helpful information or generic opinions about this product (e.g. telephone: great phone...); in the sense that the product is still in the launching phase in the market. Within time, the product becomes old. Therefore, consumers perceive the advantages/ disadvantages about each specific product feature. Therefore, they will generate comments that contain their sentiments about these features. In this paper, we present an unsupervised method to extract different product features hidden in the opinions which influence its purchase, and that combines Time Weighting (TW) which depends on the time opinions were expressed with Term Frequency-Inverse Document Frequency (TF-IDF). We conduct several experiments using two different datasets about cell phones and hotels. The results show the effectiveness of our automatic feature extraction, as well as its domain independent characteristic.

Keywords: opinion mining, product feature extraction, sentiment analysis, SentiWordNet

Procedia PDF Downloads 415