Search results for: fig fruit extract

Authors: Hafiz Muhammad Tayyab Bhatti, Munazza Usmani

Abstract:

One of nature's most destructive occurrences, floods do immense damage to communities and economic losses. Nigeria country, specifically southern Nigeria, is known for being prone to flooding. Even though periodic flooding occurs in Nigeria frequently, the floods of 2022 were the worst since those in 2012. Flood vulnerability analysis and mapping are still lacking in this region due to the very limited historical hydrological measurements and surveys on the effects of floods, which makes it difficult to develop and put into practice efficient flood protection measures. Remote sensing and Geographic Information Systems (GIS) are useful approaches to detecting, determining, and estimating the flood extent and its impacts. In this study, NOAA VIIR has been used to extract the flood extent using the flood water fraction data and afterward fused with GIS data for some zonal statistical analysis. The estimated possible flooding areas are validated using satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS). The goal is to map and studied flood extent, flood hazards, and their effects on the population, schools, and health facilities for each state of Nigeria. The resulting flood hazard maps show areas with high-risk levels clearly and serve as an important reference for planning and implementing future flood mitigation and control strategies. Overall, the study demonstrated the viability of using the chosen GIS and remote sensing approaches to detect possible risk regions to secure local populations and enhance disaster response capabilities during natural disasters.

Keywords: flood hazards, remote sensing, damage assessment, GIS, geospatial analysis

Procedia PDF Downloads 137

Authors: Shashi Bhushan, Sucharita Sen

Abstract:

In India, forest and people are inextricably linked since millions of people live adjacent to or within protected areas and harvest forest products. Indian forest has their own legacy to sustain by its own climatic nature with several social, economic and cultural activities. People surrounding forest areas are not only dependent on this resource for their livelihoods but also for the other source, like religious ceremonies, social customs and herbal medicines, which are determined by the forest like agricultural land, groundwater level, and soil fertility. The assumption that fuelwood and fodder extraction, which is the part of local livelihood leads to deforestation, has so far been the dominant mainstream views in deforestation discourses. Given the occupational division across social groups in Kaimur reserve forest, the differential nature of dependence of forest resources is important to understand. This paper attempts to assess the nature of dependence and impact of forest degradation on rural households across various social groups. Also, an additional element that is added to the enquiry is the way degradation of forests leading to scarcity of forest-based resources impacts the patterns of dependence across various social groups. Change in forest area calculated through land use land cover analysis using remote sensing technique and examination of different economic activities carried out by the households that are forest-based was collected by primary survey in Kaimur reserve forest of state of Bihar in India. The general finding indicates that the Scheduled Tribe and Scheduled Caste communities, the most socially and economically deprived sections of the rural society are involved in a significant way in collection of fuelwood, fodder, and fruits, both for self-consumption and sale in the market while other groups of society uses fuelwood, fruit, and fodder for self-use only. Depending on the local forest resources for fuelwood consumption was the primary need for all social groups due to easy accessibility and lack of alternative energy source. In last four decades, degradation of forest made a direct impact on rural community mediated through the socio-economic structure, resulting in a shift from forest-based occupations to cultivation and manual labour in agricultural and non-agricultural activities. Thus there is a need to review the policies with respect to the ‘community forest management’ since this study clearly throws up the fact that engagement with and dependence on forest resources is socially differentiated. Thus tying the degree of dependence and forest management becomes extremely important from the view of ‘sustainable’ forest resource management. The statization of forest resources also has to keep in view the intrinsic way in which the forest-dependent population interacts with the forest.

Keywords: forest degradation, livelihood, social groups, tribal community

Procedia PDF Downloads 169

Authors: Milad Abbasi

Abstract:

Carbon fiber-reinforced polymer (CFRP) composite structures are increasingly being utilized in the automotive industry due to their lightweight and specific energy absorption capabilities. Although it is impossible to predict composite mechanical properties directly using theoretical methods, various research has been conducted so far in the literature for accurate simulation of CFRP structures' energy-absorbing behavior. In this research, axial compression experiments were carried out on hand lay-up unidirectional CFRP composite tubes. The fabrication method allowed the authors to extract the material properties of the CFRPs using ASTM D3039, D3410, and D3518 standards. A neural network machine learning algorithm was then utilized to build a robust prediction model to forecast the axial compressive properties of CFRP tubes while reducing high-cost experimental efforts. The predicted results have been compared with the experimental outcomes in terms of load-carrying capacity and energy absorption capability. The results showed high accuracy and precision in the prediction of the energy-absorption capacity of the CFRP tubes. This research also demonstrates the effectiveness and challenges of machine learning techniques in the robust simulation of composites' energy-absorption behavior. Interestingly, the proposed method considerably condensed numerical and experimental efforts in the simulation and calibration of CFRP composite tubes subjected to compressive loading.

Keywords: CFRP composite tubes, energy absorption, crushing behavior, machine learning, neural network

Procedia PDF Downloads 153

Authors: Mihai Caramihai, Dan Vasilescu

Abstract:

The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.

Keywords: intelligent, control, fuzzy model, bioprocess optimization

Procedia PDF Downloads 326

Authors: Yohanes Buang, Suwari

Abstract:

Increasing interest of society in use and creation of herbal medicines has encouraged scientists/researchers to establish an ideal method to produce the best quality and quantity of pharmaceutical extracts. To have highest the antioxidative extracts, the method used must be at optimum conditions. Hence, the best method is not only able to provide highest quantity and quality of the isolated pharmaceutical extracts but also it has to be easy to do, simple, fast, and cheap. The characterization of solvents in maceration technique, in present study, involved various variables influencing quantity and quality of the pharmaceutical extracts, such as solvent’s optimum acidity-alkalinity (pH), temperature, concentration, and contact time. The shifting polarity of the solvent by combinations of water with ethanol (70:30) and (50:50) were also performed to completely record the best solvent system in application of maceration technology. Among those three solvents threated within Myrmecodia pendens, as a model of natural product, the results showed that water solvent system with conditions of alkalinity pH, optimum temperature, concentration, and contact time, is the best system to perform the maceration in order to have the highest isolated antioxidative activated extracts. The optimum conditions of the water solvent are at the alkalinity pH 9 up, 30 mg/mL of concentration, 40 min of contact time, 100 °C of temperature, and no ethanol used to replace parts of the water solvent. The present study strongly recommended the best conditions of solvent system to isolate the pharmaceutical extracts of natural products in application of the maceration technology.

Keywords: extracts, herbal medicine, natural product, maceration technique

Procedia PDF Downloads 299

Authors: Dachuan Shi, M. Hecht, Y. Ye

Abstract:

With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

Procedia PDF Downloads 131

Authors: S. S. Adamu, H. S. Muhammad, D. S. Shuaibu

Abstract:

Poor power quality in electrical power systems can lead to medical equipment at healthcare centres to malfunction and present wrong medical diagnosis. Equipment such as X-rays, computerized axial tomography, etc. can pollute the system due to their high level of harmonics production, which may cause a number of undesirable effects like heating, equipment damages and electromagnetic interferences. The conventional approach of mitigation uses passive inductor/capacitor (LC) filters, which has some drawbacks such as, large sizes, resonance problems and fixed compensation behaviours. The current trends of solutions generally employ active power filters using suitable control algorithms. This work focuses on assessing the level of Total Harmonic Distortion (THD) on medical facilities and various ways of mitigation, using radiology unit of an existing hospital as a case study. The measurement of the harmonics is conducted with a power quality analyzer at the point of common coupling (PCC). The levels of measured THD are found to be higher than the IEEE 519-1992 standard limits. The system is then modelled as a harmonic current source using MATLAB/SIMULINK. To mitigate the unwanted harmonic currents a shunt active filter is developed using synchronous detection algorithm to extract the fundamental component of the source currents. Fuzzy logic controller is then developed to control the filter. The THD without the active power filter are validated using the measured values. The THD with the developed filter show that the harmonics are now within the recommended limits.

Keywords: power quality, total harmonics distortion, shunt active filters, fuzzy logic

Procedia PDF Downloads 479

Authors: Rayan Elsiddig Eltaib, Yamanaka Norikazu, Mubarak Abdelrahman Abdalla

Abstract:

This study investigated the effects of Acacia Senegal, Calotropis procera, Leptadenia pyrotechnica, Ziziphus spina Christi, Balanites aegyptiaca, Indigofera oblongigolia, Arachis hypogea and Sesimum indicum grown in the western region of White Nile State on soil properties of the 0-10, 10-30, 30-60 and 60-90 cm depths. Soil properties were: pH(paste), electrical conductivity of the saturation extract (ECe), total N (TN), organic carbon (OC), soluble K, available P, aggregate stability and water holding capacity. Triplicate Soil samples were collected after the end of the rainy season using 5 cm diameter auger. Results indicated that pH, ECe and TN were not significantly different among plant cover types. In the top 10-30 cm depth, OC under all types was significantly higher than the control (4.1 to 7.7 fold). The highest (0.085%) OC was found under the Z. spina Christi and A. Senegal whereas the lowest (0.045%) was reported under the A. hypogea. In the 10-30 cm depth, with the exception of A. hypogea, Z. spina christi and S. indicum, P content was almost similar but significantly higher than the control by 72 to 129%. In the 10-30 cm depth, K content under the S. indicum (0.46 meq/L) was exceptionally high followed by Z. spina christi (0.102 meq/L) as compared to the control (0.029 meq/L). Water holding capacity and aggregate stability of the top 0-10 cm depth were not significantly different among plant cover types. Based on the fact that accumulation of organic matter in the soil profile of any ecosystem is an important indicator of soil quality, results of this study may conclude that (1) cultivation of A.senegal, B.aegyptiaca and Z. spina Christi improved soil quality whereas (2) cultivation of A. hypogea or soil that is solely invaded with C. procera and L.pyrotechnica may induce soil degradation.

Keywords: canopy, crops, shrubs, soil properties, trees

Procedia PDF Downloads 282

Authors: Onur Kaya, Halit Bayer

Abstract:

Global grocery and supermarket sales are among the largest markets in the world and perishable products such as fresh produce, dairy and meat constitute the biggest section of these markets. Due to their deterioration over time, the demand for these products depends highly on their freshness. They become totally obsolete after a certain amount of time causing a high amount of wastage and decreases in grocery profits. In addition, customers are asking for higher product variety in perishable product categories, leading to less predictable demand per product and to more out-dating. Effective management of these perishable products is an important issue since it is observed that billions of dollars’ worth of food is expired and wasted every month. We consider coordinated inventory and pricing decisions for perishable products with a time and price dependent random demand function. We use stochastic dynamic programming to model this system for both periodically-reviewed and continuously-reviewed inventory systems and prove certain structural characteristics of the optimal solution. We prove that the optimal ordering decision scenario has a monotone structure and the optimal price value decreases by time. However, the optimal price changes in a non-monotonic structure with respect to inventory size. We also analyze the effect of 1 different parameters on the optimal solution through numerical experiments. In addition, we analyze simple-to-implement heuristics, investigate their effectiveness and extract managerial insights. This study gives valuable insights about the management of perishable products in order to decrease wastage and increase profits.

Keywords: age-dependent demand, dynamic programming, perishable inventory, pricing

Procedia PDF Downloads 247

Authors: Sadegh Lotfieblisofla, Arash Khodabakhshi

Abstract:

Tissue plasminogen activator (tPA) as a serine protease plays an important role in the fibrinolytic system and the dissolution of fibrin clots in human body. The production of this drug in plants such as tobacco could reduce its production costs. In this study, expression of tPA gene and protein targeting to different plant cell compartments, using various signal peptides has been investigated. For high level of expression, Kozak sequence was used after CaMV35S in the beginning of the gene. In order to design the final construction, Extensin, KDEL (amino acid sequence including Lys-Asp-Glu-Leu) and SP (γ-zein signal peptide coding sequence) were used as leader signals to conduct this protein into apoplast, endoplasmic reticulum and cytosol spaces, respectively. Cloned human tPA gene under the CaMV (Cauliflower mosaic virus) 35S promoter and NOS (Nopaline Synthase) terminator into pBI121 plasmid was transferred into tobacco explants by Agrobacterium tumefaciens strain LBA₄₄₀₄. The presence and copy number of genes in transgenic tobacco was proved by Southern blotting. Enzymatic activity of the rt-PA protein in transgenic plants compared to non-transgenic plants was confirmed by Zymography assay. The presence and amount of rt-PA recombinant protein in plants was estimated by ELISA analysis on crude protein extract of transgenic tobacco using a specific antibody. The yield of recombinant tPA in transgenic tobacco for SP, KDEL, Extensin signals were counted 0.50, 0.68, 0.69 microgram per milligram of total soluble proteins.

Keywords: tPA, recombinant, transgenic, tobacco

Procedia PDF Downloads 145

Authors: Panagiotis Gkekas, Christos Sougles, Dionysios Kehagias, Dimitrios Tzovaras

Abstract:

Cooperative intelligent transport systems (C-ITS) can greatly improve safety and efficiency in road transport by enabling communication, not only between vehicles themselves but also between vehicles and infrastructure. For that reason, traffic surveillance systems on the road are of great importance. This paper focuses on the development of an on-road unit comprising several magnetic sensors for real-time vehicle detection, movement direction, and speed measurement calculations. Magnetic sensors can feel and measure changes in the earth’s magnetic field. Vehicles are composed of many parts with ferromagnetic properties. Depending on sensors’ sensitivity, changes in the earth’s magnetic field caused by passing vehicles can be detected and analyzed in order to extract information on the properties of moving vehicles. In this paper, we present a prototype algorithm for real-time, high-accuracy, vehicle detection, and speed measurement, which can be implemented as a portable, low-cost, and non-invasive to existing infrastructure solution with the potential to replace existing high-cost implementations. The paper describes the algorithm and presents results from its preliminary lab testing in a close to real condition environment. Acknowledgments: Work presented in this paper was co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation (call RESEARCH–CREATE–INNOVATE) under contract no. Τ1EDK-03081 (project ODOS2020).

Keywords: magnetic sensors, vehicle detection, speed measurement, traffic surveillance system

Procedia PDF Downloads 122

Authors: Min Chen, Rubi Gupta

Abstract:

Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

Procedia PDF Downloads 156

Authors: Meenakshi Verma, Mandeep Singh Bakshi, Kultar Singh

Abstract:

Magnetic nanoparticles have received incredible importance in view of their diverse applications, which arise primarily due to their response to the external magnetic field. The magnetic behaviour of magnetic nanoparticles (NPs) helps them in numerous different ways. The most important amongst them is the ease with which they can be purified and also can be separated from the media in which they are present merely by applying an external magnetic field. This exceptional ease of separation of the magnetic NPs from an aqueous media enables them to use for extracting/removing metal pollutants from complex aqueous medium. Functionalized magnetic NPs can be subjected for the metallic impurities extraction if are favourably adsorbed on the NPs surfaces. We have successfully used the magnetic NPs as vehicles for gold and silver NPs removal from the complex fluids. The NPs loaded with gold and silver NPs pollutant fractions has been easily removed from the aqueous media by using external magnetic field. Similarly, we have used the magnetic NPs for extraction of protein from complex media and then constantly washed with pure water to eliminate the unwanted surface adsorbed components for quantitative estimation. The purified and protein loaded magnetic NPs are best analyzed with SDS Page to not only for characterization but also for separating the protein fractions. A collective review of the results indicates that we have synthesized surfactant coated iron oxide NPs and then functionalized these with selected materials. These surface active magnetic NPs work very well for the extraction of metallic NPs from the aqueous bulk and make the whole process environmentally sustainable. Also, magnetic NPs-Au/Ag/Pd hybrids have excellent protein extracting properties. They are much easier to use in order to extract the magnetic impurities as well as protein fractions under the effect of external magnetic field without any complex conventional purification methods.

Keywords: magnetic nanoparticles, protein, functionalized, extraction

Procedia PDF Downloads 100

Authors: Vanessa G. P. Severino, JOÃO Gabriel M. Junqueira, Michelle N. G. do Nascimento, Francisco W. B. Aquino, João B. Fernandes, Ana P. Terezan

Abstract:

The scientific interest in analyzing VOCs represents a significant modern research field as a result of importance in most branches of the present life and industry. Therefore it is extremely important to investigate, identify and isolate volatile substances, since they can be used in different areas, such as food, medicine, cosmetics, perfumery, aromatherapy, pesticides, repellents and other household products through methods for extracting volatile constituents, such as solid phase microextraction (SPME), hydrodistillation (HD), solvent extraction (SE), Soxhlet extraction, supercritical fluid extraction (SFE), stream distillation (SD) and vacuum distillation (VD). The Chemometrics is an area of chemistry that uses statistical and mathematical tools for the planning and optimization of the experimental conditions, and to extract relevant chemical information multivariate chemical data. In this context, the focus of this work was the study of the chemical VOCs by SPME of the specie X. aromatica, in search of constituents that can be used in the industrial sector as well as in food, cosmetics and perfumery, since these areas industrial has a considerable role. In addition, by chemometric analysis, we sought to maximize the answers of this research, in order to search for the largest number of compounds. The investigation of flowers from X. aromatica in vitro and in alive mode proved consistent, but certain factors supposed influence the composition of metabolites, and the chemometric analysis strengthened the analysis. Thus, the study of the chemical composition of X. aromatica contributed to the VOCs knowledge of the species and a possible application.

Keywords: chemometrics, flowers, HS-SPME, Xylopia aromatica

Procedia PDF Downloads 362

Authors: Eric Beyegue, Boris Azantza, Judith Laure Ngondi, Julius E. Oben

Abstract:

Background: It is clearly that phytochemical constituents of plants in relation exhibit free radical scavenging, antioxidant and glycosylation properties. This study investigated the in vitro antioxidant and free radical scavenging, inhibited activities against α-amylase and invertase enzymes of stem bark extracts C. edulis (Olacaceae). Methods: Four extracts (hexane, dichloromethane, ethanol and aqueous) from the barks of C. edulis were used in this study. Colorimetric in vitro methods were using for evaluate free radical scavenging activity DPPH, ABTS, NO, OH, antioxidant capacity, glycosylation activity, inhibition of α-amylase and invertase activities, phenolic, flavonoid and alkaloid contents. Results: C. edulis extracts (CEE) had a higher scavenging potential on the 2, 2-diphenyl-1-picrylhydrazyl (DPPH), hydroxyl (OH), nitrite oxide (NO), 2, 2-azinobis (3-ethylbenzthiazoline)-6-sulfonic acid (ABTS) radicals and glucose scavenging with the IC50 varied between 41.95 and 36694.43 µg/ml depending on the solvent of extraction. The ethanol extract of C. edulis stem bark (CE EtOH) showed the highest polyphenolic (289.10 + 30.32), flavonoid (1.12 + 0.09) and alkaloids (18.47 + 0.16) content. All the tested extracts demonstrated a relative high inhibition potential against α-amylase and invertase digestive enzymes activities. Conclusion: This study suggests that CEE exhibited higher antioxidant potential and significant inhibition potential against digestive enzymes.

Keywords: Coula edulis, antioxidant, scavenging activity, amylase, invertase

Procedia PDF Downloads 351

Authors: Syed Farooq Adil, Merajuddinkhan, Mujeeb Khan, Hamad Z. Alkhathlan

Abstract:

Phytochemicals from plant extracts belong to an important source of natural products which have demonstrated excellent cytotoxic activities. However, plants of different origins exhibit diverse chemical compositions and bioactivities. Therefore, the discovery of plants based new anticancer agents from different parts of the world is always challenging. In this study, methanolic extracts of different parts of 11 plants from Saudi Arabia have been tested in vitro for their anticancer potential on human liver cancer cell line (HepG2). Particularly, for this study, plants from Asteraceae, Resedaceae, and Polygonaceae families were chosen on the basis of locally available ethnobotanical data and their medicinal properties. Among 12 tested extract samples, three samples obtained from Artemisia monosperma stem, Ochradenus baccatus aerial parts, and Pulicaria glutinosa stem have demonstrated interesting cytotoxic activities with a cell viability of 29.3%, 28.4% and 24.2%, respectively. Whereas, four plant extracts including Calendula arvensis aerial parts, Scorzonera musilii whole plant, A. monosperma leaves show moderate anticancer properties bearing a cell viability ranging from 11.9 to 16.7%. The remaining extracts have shown poor cytotoxic activities. Subsequently, GC-MS analysis of methanolic extracts of the four most active plants extracts such as C. comosum, O. baccatus, P. glutinosa and A. monosperma detected the presence of 41 phytomolecules. Among which 3-(4-hydroxyphenyl) propionitrile (1), 8,11-octadecadiynoic acid methyl ester (2), 6,7-dimethoxycoumarin (3), and 1-(2-hydroxyphenyl) ethenone (4) were found to be the lead compounds of C. comosum, O. baccatus P. glutinosa and A. monosperma, respectively.

Keywords: medicinal plants, asteraceae, polygonaceae, hepg2

Procedia PDF Downloads 127

Authors: Hira Jabbar

Abstract:

Education is vital for inclusive growth of an economy and a critical contributor for investment in human capital. Like other developing countries, Pakistan is facing enormous challenges regarding the provision of public facilities, improper infrastructure planning, accelerating rate of population and poor accessibility. The influence of the rapid advancement and innovations in GIS and RS techniques have proved to be a useful tool for better planning and decision making to encounter these challenges. Therefore present study incorporates GIS and RS techniques to investigate the spatial distribution of school facilities, identifies settlements with served and unserved population, finds potential areas for new schools based on population and develops an accessibility index to evaluate the higher accessibility for schools. For this purpose high-resolution worldview imagery was used to develop road network, settlements and school facilities and to generate school accessibility for each level. Landsat 8 imagery was utilized to extract built-up area by applying pre and post-processing models and Landscan 2015 was used to analyze population statistics. Service area analysis was performed using network analyst extension in ArcGIS 10.3v and results were evaluated for served and underserved areas and population. An accessibility tool was used to evaluate a set of potential destinations to determine which is the most accessible with the given population distribution. Findings of the study may contribute to facilitating the town planners and education authorities for understanding the existing patterns of school facilities. It is concluded that GIS and remote sensing can be effectively used in urban transport and facility planning.

Keywords: accessibility, geographic information system, landscan, worldview

Procedia PDF Downloads 325

Authors: Ramiro Quintanilla-Licea, Isvar K. Angeles-Hernandez, Javier Vargas-Villarreal

Abstract:

Amebiasis caused by Entamoeba histolytica, associated with high morbidity and mortality, is currently a significant public health problem worldwide, especially in developing countries. In the world, around 50 million people develop this illness, and up to 100,000 deaths occur annually. Due to the side-effects and the resistance that pathogenic protozoa show against common antiparasitic drugs (e.g., metronidazole), growing attention has been paid to plants used in traditional medicine around the world to find new antiprotozoal agents. In this study is reported about the isolation and structure elucidation of antiamoebic compounds occurring in Lippia graveolens Kunth (Mexican oregano). The work-up of the methanol extract of L. graveolens afforded the known flavonoids pinocembrin (1), sakuranetin (2), cirsimaritin (3) and naringenin (4) by bioguided isolation using several chromatographic techniques. Structural elucidation of the isolated compounds was based on spectroscopic/spectrometric analyses (IR; 1H- and 13C-NMR; MS) and comparison with literature data. These compounds showed significant antiprotozoal activity against Entamoeba histolytica trophozoites using in vitro tests (positive control metronidazole IC50 0.205 µg/mL). The antiprotozoal activity of pinocembrin and naringenin (IC50 of 29.51 µg/mL and 28.85 µg/mL, respectively) was higher compared with sakuranetin (44.47 µg/mL) and with cirsimaritin (150.00 µg/mL), revealing that a 5,7-dihydroxylated A ring is essential for antiprotozoal activity. These research funds may validate the use of this plant in the traditional Mexican medicine for the treatment of some digestive disorders and can help to integrate the use of extracts of L. graveolens in the conventional and complementary medicine for the treatment of parasitic diseases.

Keywords: amoebiasis, antiprotozoal agents, bioguided isolation, infectious diseases

Procedia PDF Downloads 189

Authors: A. A. Adedini, B. A. Aina, P. U. Ogbo

Abstract:

Child obesity is on the rise globally. According to the World Health Organization, the number of obese children would increase to 70 million by 2025 if no intervention is made. An increase in the prevalence of overweight and obesity amongst school children in Lagos State, Nigeria has been established but specific factors promoting its prevalence are unknown. This aim of this study is to identify the commonly expressed factor(s) responsible for the rise in prevalence of child overweight and obesity in Lagos, Nigeria. Five focus group discussions were conducted with different groups of stake-holders involved in child care, namely: parents, teachers and health workers. Participants were recruited using a purposive sampling method; a validated question guide was employed for the discussion sessions. The discussions were recorded, collated, analysed using Grounded theory to extract themes. Six themes emerged from the discussions as follows: Civilization and lifestyle imbalance resulting from busy work schedules of young mothers leading to adoption of westernized culture promoting preference for processed and fast food meals; insecurity and congestion of the state which discourages out-door activities; ignorance of the populace on the prevalence of child obesity in the state; inadequate educative and enlightenment programmes in schools and by the Nigerian government; myths on child care and body physique and societal perceptions of the children born into affluent homes. Some of the factors responsible for the rise in the prevalence of child obesity in Lagos, Nigeria have been identified. Preventive strategies to control the prevalence of obesity in children residing in Lagos state is considered for further studies.

Keywords: Childhood Obesity, factors, lagos state, stakeholders

Procedia PDF Downloads 375

Authors: Claudia Ehrentraut, Osama Ibrahim, Hercules Dalianis

Abstract:

Policy making situations are real-world problems that exhibit complexity in that they are composed of many interrelated problems and issues. To be effective, policies must holistically address the complexity of the situation rather than propose solutions to single problems. Formulating and understanding the situation and its complex dynamics, therefore, is a key to finding holistic solutions. Analysis of text based information on the policy problem, using Natural Language Processing (NLP) and Text analysis techniques, can support modelling of public policy problem situations in a more objective way based on domain experts knowledge and scientific evidence. The objective behind this study is to support modelling of public policy problem situations, using text analysis of verbal descriptions of the problem. We propose a formal methodology for analysis of qualitative data from multiple information sources on a policy problem to construct a causal diagram of the problem. The analysis process aims at identifying key variables, linking them by cause-effect relationships and mapping that structure into a graphical representation that is adequate for designing action alternatives, i.e., policy options. This study describes the outline of an algorithm used to automate the initial step of a larger methodological approach, which is so far done manually. In this initial step, inferences about key variables and their interrelationships are extracted from textual data to support a better problem structuring. A small prototype for this step is also presented.

Keywords: public policy, problem structuring, qualitative analysis, natural language processing, algorithm, inference extraction

Procedia PDF Downloads 589

Authors: Dian Muzdalifah, Anastasia F. Devi, Zatil A. Athaillah, Linar Z. Udin

Abstract:

Tempe is a functional food prepared from soybeans through Rhizopus spp fermentation. It is well known as functional food, originated from Indonesia. Most studies on tempe functionalities refer to ripe (48 h fermentation) tempe and only limited studies discuss overripe tempe while longer fermentation time possibly increased tempe health benefit. Hence, the present study was performed to investigate the cytotoxic activity againts MCF-7 breast cancer cells and antioxidant property of tempe prepared from 0–156 h of fermentation. Tempe samples were dried and extracted with acetone and ethanol, respectively. Their extracts were used for subsequent analysis. The cytotoxic activity was assessed on MCF 7 breast cancer cells using Alamar Blue method. The antioxidant activity was determined by DPPH free radical scavenging assay. The results indicated that acetone extracts of 108 h tempe had a potent cytotoxic activity against MCF-7 breast cancer cells (IC50 = 2.54 ± 0,30 μg/mL). Ethanol extracts of 108 h tempe also showed the potency, but at slightly higher IC50 (5.20 ± 1.01 μg/mL). Both acetone and ethanol extracts of 108 and 120 h tempe showed high antioxidant activity expressed as percent inhibition with no significant difference. However, acetone extracts of 120 h tempe (81.31 ± 3.70 %) had better ability to inhibit oxidation reaction than that of ethanol extracts (75.77 ± 6.00 %). It can be concluded that the cytotoxic activity of tempe from 0–156 h of fermentation is positively correlated to their corresponding antioxidant property. Longer fermentation time, up to 108 h, increased the ability of tempe to inhibit the growth of MCF-7 breast cancer cells and oxidative reaction. But extended fermentation time, up to 156 h, tends to decrease its ability. Further studies are encouraged to identify the active components contained in each extract.

Keywords: antioxidant property, cytotoxic activity, extracts, overripe tempeh

Procedia PDF Downloads 277

Authors: Jiaying Gao, Thammananya Sakcharoen, Wilailuk Niyommaneerat

Abstract:

Haikou is the capital of Hainan, a major tourism province in China with rich ecotourism resources. There is a need to strengthen tourism destination management in Haikou toward sustainable development as a tourism city. The purpose of this study was to investigate the relationship between tourism destination management and sustainable tourism in Haikou. Exploratory factor analysis was used to extract six dimensions of this study. Three dimensions (10 factors) of tourism destination management were analyzed in terms of economic development, social and cultural development, and conservation of ecosystem. Sustainability awareness, tourism development experience, and tourism public infrastructure in three dimensions (12 factors) of sustainable tourism. There were 426 questionnaire respondents, including 225 tourists, 172 residents, 12 tourism agency persons, 10 government persons, 3 self-employed, and 4 others. The Structural equation modeling (SEM) model was finally conducted to test the hypotheses empirically and explore the impact relationship. The study found a significant relationship between tourism destination management and sustainable tourism: social and cultural development had the greatest significant positive impact on the tourism development experience (0.788***). Social and cultural development also showed a significant positive impact and great impetus on tourism public infrastructure (0.561***). A negative effect relationship (-0.096***) emerged between ecosystem conversion and tourism development experience. It showed a positive relationship between economic development and social and cultural development of tourism destination management in promoting sustainable tourism. There are still some gaps for improvement, such as the need for sustainable ecological management to promote local sustainable tourism trends and enhance tourism experience development, which may require a long-term process of mitigation.

Keywords: Haikou (Hainan, China), influence relationship, sustainable tourism, tourism destination management

Procedia PDF Downloads 139

Authors: Vicky Khasandi-Telewa, Sinfree Makoni

Abstract:

This paper examines the lived experiences of Kenyans caught between the two main varieties of English and the communication challenges they often face. The paper aims to provide evidence for the challenges that Kenyan speakers of English have experienced as a result of the confluence between British English (BrE) and American English (AmE). The study is explorative thus, qualitative and a descriptive research design was used. The objectives were to describe the communication challenges Kenyans encounter due to the differences in grammar, pronunciation, vocabulary, and pragmatics between AmE and BrE and, to illuminate these variations to enable the Kenyan English learner to communicate appropriately. The purposive sample consisted of sixty five subjects, all who were from a top girls national high school in Kenya, therefore, many are in high-end positions nationally and internationally and well-travelled; in fact, seven are based in the USA, two in the United Kingdom and one lives in Australia. Using interviews, they were asked about their experiences with the different varieties of English, and their responses recorded. Autoethnography, a qualitative research method that involves introspection and cultural analysis, was also used. Thematic content analysis was used to extract the themes and group them for data analysis. The theoretical framework used is World Englishes by Kachru. The results indicate that there is indeed some communication breakdown due to linguistic varieties, but the differences are largely understood by speakers of the different varieties. Attitude plays a major role in communication challenges between the different Englishes, especially among teachers. The study urges acceptance of different varieties of English so long as communication takes place. This has implications for teaching English to Kenyan and speakers of other languages to whom English is taught as a Second Language or Foreign language.

Keywords: American english, british english, kenyan english, englishes, teaching of english to speakers of other languages (TeSOL)

Procedia PDF Downloads 71

Authors: Matthew Omoniyi Adebola, Jude E Amadi

Abstract:

Ground nut (Arachis hypogaea) is one of the most popular commercial crops in Nigeria. Its suc-cessful production has been drastically affected by early leaf spot disease caused by Mycosphae-rella arachidis Deighton. In vitro control of the pathogen by six medicinal plants (Entada afri-cana, Vitex doniana, Lawsonia inermis, Azadirachta indica, Acalypha hispida and Nuaclea lati-folia) was assessed in this study. The extracts of the plants were prepared using cold and hot wa-ter and alcohol. The pathogen was isolated from ground nut infected with early leaf spot disease. The results revealed a great significant difference (P<0.05) in yield of extracts between cold water, hot water, and alcohol extracts. A significant difference (P<0.05) was observed in percentage concentrations of the various phytochemical constituents present in the extracts. Flavonoids per-centage concentration was the highest (0.68 - 1.95%) followed by saponnin(0.09-1.53%) in N. latifolia extracts. Steroiods had the least percentage concentrations (0.00- 0.09%)followed by terpenoids(0.02–0.71%) and proanthocyannin (0.05 – 0.86%). N. latifolia extracts produced the highest percentage concentrations (0.07–1.95%) of all the phytochemicals followed by A. indi-ca(0.05–1.64%)and least concentrations were obtained in A. hispidia(0.09 – 0.87%)and V. do-niana (0.00–0.88%). The extracts inhibited spore germination and growth of M. arachidis. The inhibition by alcohol extracts was high and significantly different (P>0.05) from cold and hot water extracts. Alcohol extract of L. inermis gave 100% spore germination inhibition followed by N. latifolia and A.indica with 97.75% and 85.60% inhibition respectively. Therefore, field trials of these six medicinal plants on the control of early leaf spot disease of ground nut are rec-ommended.

Keywords: groundnut, phytochemicals, medicinal plants, extracts, inhibition

Procedia PDF Downloads 297

Authors: Spandana Ramisetty, Mandan Chidambaram, Ramesh Bhujade

Abstract:

Algal biomass is not only a potential source for biocrude but also for high value chemicals like carotenoids, fatty acids, proteins, polysaccharides, vitamins etc. Astaxanthin is one such high value vital carotenoid which has extensive applications in pharmaceutical, aquaculture, poultry and cosmetic industries and expanding as dietary supplement to humans. Green microalgae Haematococcus pluvialis is identified as the richest natural source of astaxanthin and is the key source of commercial astaxanthin. Several extraction processes from wet and dry Haematococcus pluvialis biomass have been explored by researchers. Extraction with supercritical CO₂ and various physical disruption techniques like mortar and pestle, homogenization, ultrasonication and ball mill from dried algae are widely used extraction methods. However, these processes require energy intensive drying of biomass that escalates overall costs notably. From the process economics perspective, it is vital to utilize wet processing technology in order to eliminate drying costs. Hydrothermal liquefaction (HTL) is a thermo-chemical conversion process that converts wet biomass containing over 80% water to bio-products under high temperature and high pressure conditions. Astaxanthin is a lipid soluble pigment and is usually extracted along with lipid component. Mild HTL at 200°C and 60 bar has been demonstrated by researchers in a microfluidic platform achieving near complete extraction of astaxanthin from wet biomass. There is very limited work done in this field. An integrated approach of sequential HTL offers cost-effective option to extract astaxanthin/lipid from wet algal biomass without drying algae and also recovering water, minerals and nutrients. This paper reviews past work and evaluates the astaxanthin extraction processes with focus on hydrothermal extraction.

Keywords: astaxanthin, extraction, high value chemicals, hydrothermal liquefaction

Procedia PDF Downloads 307

Authors: Yumeng Ma, Fang Wang, Jinxia Huang

Abstract:

Researchers put forward higher requirements for efficient acquisition and utilization of domain knowledge in the big data era. As literature is an effective way for researchers to quickly and accurately understand the research situation in their field, the knowledge discovery based on literature has become a new research method. As a tool to organize and manage knowledge in a specific domain, the subject knowledge base can be used to mine and present the knowledge behind the literature to meet the users' personalized needs. This study designs the construction route of the subject knowledge base for specific research problems. Information extraction method based on knowledge engineering is adopted. Firstly, the subject knowledge model is built through the abstraction of the research elements. Then under the guidance of the knowledge model, extraction rules of knowledge points are compiled to analyze, extract and correlate entities, relations, and attributes in literature. Finally, a database platform based on this structured knowledge is developed that can provide a variety of services such as knowledge retrieval, knowledge browsing, knowledge q&a, and visualization correlation. Taking the construction practices in the field of activating blood circulation and removing stasis as an example, this study analyzes how to construct subject knowledge base based on literature knowledge extraction. As the system functional test shows, this subject knowledge base can realize the expected service scenarios such as a quick query of knowledge, related discovery of knowledge and literature, knowledge organization. As this study enables subject knowledge base to help researchers locate and acquire deep domain knowledge quickly and accurately, it provides a transformation mode of knowledge resource construction and personalized precision knowledge services in the data-intensive research environment.

Keywords: knowledge model, literature knowledge extraction, precision knowledge services, subject knowledge base

Procedia PDF Downloads 163

Authors: Iman A. Saad, Loay E. George

Abstract:

Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

Procedia PDF Downloads 335

Authors: Chih Jou Hsiao, Chung Ming Lo, Li Chun Hsieh

Abstract:

Brain tumor is not the cancer having high incidence rate, but its high mortality rate and poor prognosis still make it as a big concern. On clinical examination, the grading of brain tumors depends on pathological features. However, there are some weak points of histopathological analysis which can cause misgrading. For example, the interpretations can be various without a well-known definition. Furthermore, the heterogeneity of malignant tumors is a challenge to extract meaningful tissues under surgical biopsy. With the development of magnetic resonance imaging (MRI), tumor grading can be accomplished by a noninvasive procedure. To improve the diagnostic accuracy further, this study proposed a computer-aided diagnosis (CAD) system based on MRI features to provide suggestions of tumor grading. Gliomas are the most common type of malignant brain tumors (about 70%). This study collected 34 glioblastomas (GBMs) and 73 lower-grade gliomas (LGGs) from The Cancer Imaging Archive. After defining the region-of-interests in MRI images, multiple quantitative morphological features such as region perimeter, region area, compactness, the mean and standard deviation of the normalized radial length, and moment features were extracted from the tumors for classification. As results, two of five morphological features and three of four image moment features achieved p values of <0.001, and the remaining moment feature had p value <0.05. Performance of the CAD system using the combination of all features achieved the accuracy of 83.18% in classifying the gliomas into LGG and GBM. The sensitivity is 70.59% and the specificity is 89.04%. The proposed system can become a second viewer on clinical examinations for radiologists.

Keywords: brain tumor, computer-aided diagnosis, gliomas, magnetic resonance imaging

Procedia PDF Downloads 260

Authors: Roghaieh Parvizsedghy, Seyed Mojtaba Sadrameli

Abstract:

Diminishing oil reserves, deteriorating health standards because of greenhouse gas emissions and associated environmental impacts have emerged biofuel production. Vegetable oils are proved to be valuable feedstock in these growing industries as they are renewable and potentially inexhaustible sources. Thermal Cracking of vegetable oils (triglycerides) leads to production of biofuels which are similar to fossil fuels in terms of composition but their combustion and physical properties have limits. Acrolein (very poisonous gas) and water production during cracking of triglycerides occurs because of presence of glycerin in their molecular structure. Transesterification of vegetable oil is a method to extract glycerol from triglycerides structure and produce methyl ester. In this study, castor methyl ester was used for thermal cracking in order to survey the efficiency of this method to produce bio-gasoline and bio-diesel. Thus, several experiments were designed by means of central composite method. Statistical studies showed that two reaction parameters, namely cracking temperature and feed flowrate, affect products yield significantly. At the optimized conditions (480 °C and 29 g/h) for maximum bio-gasoline production, 88.6% bio-oil was achieved which was distilled and separated as bio-gasoline (28%) and bio-diesel (48.2%). Bio-gasoline exposed a high octane number and combustion heat. Distillation curve and Reid vapor pressure of bio-gasoline fell in the criteria of standard gasoline (class AA) by ASTM D4814. Bio-diesel was compatible with standard diesel by ASTM D975. Water production was negligible and no evidence of acrolein production was distinguished. Therefore, thermal cracking of castor methyl ester could be used as a method to produce valuable biofuels.

Keywords: bio-diesel, bio-gasoline, castor methyl ester, thermal cracking, transesterification

Procedia PDF Downloads 240

Authors: Chien-Chun Huang, P. W. Yuan

Abstract:

Banana is one of the important fruits which constitute a valuable source of energy, vitamins and minerals and an important food component throughout the world. The fruit ripening and maturity standards vary from country to country depending on the expected shelf life of market. During ripening there are changes in appearance, texture and chemical composition of banana. The changes of component of banana during ethylene-induced ripening are categorized as nutritive values and commercial utilization. The objectives of this study were to investigate the changes of chemical composition and physicochemical properties of banana during ethylene-induced ripening. Green bananas were harvested and ripened by ethylene gas at low temperature (15℃) for seven stages. At each stage, banana was sliced and freeze-dried for banana flour preparation. The changes of total starch, resistant starch, chemical compositions, physicochemical properties, activity of amylase, polyphenolic oxidase (PPO) and phenylalanine ammonia lyase (PAL) of banana were analyzed each stage during ripening. The banana starch was isolated and analyzed for gelatinization properties, pasting properties and microscopic appearance each stage of ripening. The results indicated that the highest total starch and resistant starch content of green banana were 76.2% and 34.6%, respectively at the harvest stage. Both total starch and resistant starch content were significantly declined to 25.3% and 8.8%, respectively at the seventh stage. Soluble sugars content of banana increased from 1.21% at harvest stage to 37.72% at seventh stage during ethylene-induced ripening. Swelling power of banana flour decreased with the progress of ripening stage, but solubility increased. These results strongly related with the decreases of starch content of banana flour during ethylene-induced ripening. Both water insoluble and alcohol insoluble solids of banana flour decreased with the progress of ripening stage. Both activity of PPO and PAL increased, but the total free phenolics content decreased, with the increases of ripening stages. As ripening stage extended, the gelatinization enthalpy of banana starch significantly decreased from 15.31 J/g at the harvest stage to 10.55 J/g at the seventh stage. The peak viscosity and setback increased with the progress of ripening stages in the pasting properties of banana starch. The highest final viscosity, 5701 RVU, of banana starch slurry was found at the seventh stage. The scanning electron micrograph of banana starch showed the shapes of banana starch appeared to be round and elongated forms, ranging in 10-50 μm at the harvest stage. As the banana closed to ripe status, some parallel striations were observed on the surface of banana starch granular which could be caused by enzyme reaction during ripening. These results inferred that the highest resistant starch was found in the green banana could be considered as a potential application of healthy foods. The changes of chemical composition and physicochemical properties of banana could be caused by the hydrolysis of enzymes during the ethylene-induced ripening treatment.

Keywords: maturation of banana, appearance, texture, soluble sugars, resistant starch, enzyme activities, physicochemical properties of banana starch

Procedia PDF Downloads 318