Search results for: natural extract
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7421

Search results for: natural extract

3641 Electrochemical Biosensor for the Detection of Botrytis spp. in Temperate Legume Crops

Authors: Marzia Bilkiss, Muhammad J. A. Shiddiky, Mostafa K. Masud, Prabhakaran Sambasivam, Ido Bar, Jeremy Brownlie, Rebecca Ford

Abstract:

A greater achievement in the Integrated Disease Management (IDM) to prevent the loss would result from early diagnosis and quantitation of the causal pathogen species for accurate and timely disease control. This could significantly reduce costs to the growers and reduce any flow on impacts to the environment from excessive chemical spraying. Necrotrophic fungal disease botrytis grey mould, caused by Botrytis cinerea and Botrytis fabae, significantly reduce temperate legume yield and grain quality during favourable environmental condition in Australia and worldwide. Several immunogenic and molecular probe-type protocols have been developed for their diagnosis, but these have varying levels of species-specificity, sensitivity, and consequent usefulness within the paddock. To substantially improve speed, accuracy, and sensitivity, advanced nanoparticle-based biosensor approaches have been developed. For this, two sets of primers were designed for both Botrytis cinerea and Botrytis fabae which have shown the species specificity with initial sensitivity of two genomic copies/µl in pure fungal backgrounds using multiplexed quantitative PCR. During further validation, quantitative PCR detected 100 spores on artificially infected legume leaves. Simultaneously an electro-catalytic assay was developed for both target fungal DNA using functionalised magnetic nanoparticles. This was extremely sensitive, able to detect a single spore within a raw total plant nucleic acid extract background. We believe that the translation of this technology to the field will enable quantitative assessment of pathogen load for future accurate decision support of informed botrytis grey mould management.

Keywords: biosensor, botrytis grey mould, sensitive, species specific

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3640 Smart Cities, Morphology of the Uncertain: A Study on Development Processes Applied by Amazonian Cities in Ecuador

Authors: Leonardo Coloma

Abstract:

The world changes constantly, every second its properties vary due either natural factors or human intervention. As the most intelligent creatures on the planet, human beings have transformed the environment and paradoxically –have allowed ‘mother nature’ to lose species, accelerate the processes of climate change, the deterioration of the ozone layer, among others. The rapid population growth, the procurement, administration and distribution of resources, waste management, and technological advances are some of the factors that boost urban sprawl whose gray stain extends over the territory, facing challenges such as pollution, overpopulation and scarcity of resources. In Ecuador, these problems are added to the social, cultural, economic and political anomalies that have historically affected it. This fact can represent a greater delay when trying to solve global problems, without having paid attention to local inconveniences –smaller ones, but ones that could be the key to project smart solutions on bigger ones. This research aims to highlight the main characteristics of the development models adopted by two Amazonian cities, and analyze the impact of such urban growth on society; to finally define the parameters that would allow the development of an intelligent city in Ecuador, prepared for the challenges of the XXI Century. Contrasts in the climate, temperature, and landscape of Ecuadorian cities are fused with the cultural diversity of its people, generating a multiplicity of nuances of an indecipherable wealth. However, we strive to apply development models that do not recognize that wealth, not understanding them and ignoring that their proposals will vary according to where they are applied. Urban plans seem to take a bit of each of the new theories and proposals of development, which, in the encounter with the informal growth of cities, with those excluded and ‘isolated’ societies, generate absurd morphologies - where the uncertain becomes tangible. The desire to project smart cities is ever growing, but it is important to consider that this concept does not only have to do with the use of information and communication technologies. Its success is achieved when advances in science and technology allow the establishment of a better relationship between people and their context (natural and built). As a research methodology, urban analysis through mappings, diagrams and geographical studies, as well as the identification of sensorial elements when living the city, will make evident the shortcomings of the urban models adopted by certain populations of the Ecuadorian Amazon. Following the vision of previous investigations started since 2014 as part of ‘Centro de Acciones Urbanas,’ the results of this study will encourage the dialogue between the city (as a physical fact) and those who ‘make the city’ (people as its main actors). This research will allow the development of workshops and meetings with different professionals, organizations and individuals in general.

Keywords: Latin American cities, smart cities, urban development, urban morphology, urban sprawl

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3639 Design Development, Fabrication, and Preliminary Specifications of Multi-Fingered Prosthetic Hand

Authors: Mogeeb A. El-Sheikh

Abstract:

The study has developed the previous design of an artificial anthropomorphic humanoid hand and accustomed it as a prosthetic hand. The main specifications of this design are determined. The development of our previous design involves the main artificial hand’s parts and subassemblies, palm, fingers, and thumb. In addition, the study presents an adaptable socket design for a transradial amputee. This hand has 3 fingers and thumb. It is more reliable, cosmetics, modularity, and ease of assembly. Its size and weight are almost as a natural hand. The socket cavity has the capability for different sizes of a transradial amputee. The study implements the developed design by using rapid prototype and specifies its main specifications by using a data glove and finite element method.

Keywords: adaptable socket, prosthetic hand, transradial amputee, data glove

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3638 Chemical Risk Posed by Hospital Liquid Effluents Example CHU Beni Messous Algiers

Authors: Laref Nabil

Abstract:

Ecology is at the center of many debates and international regulations. It therefore becomes a necessity and a privileged axis in many countries policy. The rise of environmental problems, the particularism of the hospital as an actor Public Health must lead by example in hygiene, prevention of risks to man and his environment. In this, it seemed interesting to make a poster on hospital liquid effluents in order to know not only the regulatory aspects but also their degree of pollution and their management in health institutions. Materials and methods: Samples taken at several looks, analysis performed at STEP Reghaia Algiers. Discussion and / or findings: In general, central gaze analysis results of water we can conclude that the contents of the various physico-chemical parameters greatly exceed the standards. Although the hypothesis of assimilating hospital liquid effluents domestic waters is confirmed, the liquid effluent from the University Hospital of Beni Messous and dumped in the natural environment still represent ecotoxicological risk.

Keywords: health, hospital, liquid effluents, water

Procedia PDF Downloads 443
3637 Searching Linguistic Synonyms through Parts of Speech Tagging

Authors: Faiza Hussain, Usman Qamar

Abstract:

Synonym-based searching is recognized to be a complicated problem as text mining from unstructured data of web is challenging. Finding useful information which matches user need from bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration to realize the technique. Parts-of-Speech tagging is applied for pattern generation of the query and a thesaurus for this experiment was formed and used. Comparison with Non-Context Based Searching, Context Based searching proved to be a more efficient approach while dealing with linguistic semantics. This approach is very beneficial in doing intent based searching. Finally, results and future dimensions are presented.

Keywords: natural language processing, text mining, information retrieval, parts-of-speech tagging, grammar, semantics

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3636 Simple and Concise Maximum Power Control Circuit for PV Power Generation

Authors: Keiju Matsui, Mikio Yasubayashi, Masayoshi Umeno

Abstract:

Consumption of energy is increasing every year, and yet does not the decline at all. The main energy source is fossil fuels such as petroleum and natural gas. Since it is the finite resources, they will be exhausted someday. Moreover, to make the fossil fuel an energy source causes an environment problem. In such way, one solution of the problems is the solar battery that is remarkable as one of the alternative energies. Under such circumstances, in this paper, we propose a novel maximum power control circuit for photovoltaic power generation system with simple and fast-response operation. In addition to an application to the solar battery, since this control system is possible to operate with simple circuit and fast-response, the polar value control like the maximum or the minimum value tracking for general application could be easily realized.

Keywords: maximum power control, inter-connection, photovoltaic power generation, PI controller, multiplier, exclusive-or, power system

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3635 Blue Economy and Marine Mining

Authors: Fani Sakellariadou

Abstract:

The Blue Economy includes all marine-based and marine-related activities. They correspond to established, emerging as well as unborn ocean-based industries. Seabed mining is an emerging marine-based activity; its operations depend particularly on cutting-edge science and technology. The 21st century will face a crisis in resources as a consequence of the world’s population growth and the rising standard of living. The natural capital stored in the global ocean is decisive for it to provide a wide range of sustainable ecosystem services. Seabed mineral deposits were identified as having a high potential for critical elements and base metals. They have a crucial role in the fast evolution of green technologies. The major categories of marine mineral deposits are deep-sea deposits, including cobalt-rich ferromanganese crusts, polymetallic nodules, phosphorites, and deep-sea muds, as well as shallow-water deposits including marine placers. Seabed mining operations may take place within continental shelf areas of nation-states. In international waters, the International Seabed Authority (ISA) has entered into 15-year contracts for deep-seabed exploration with 21 contractors. These contracts are for polymetallic nodules (18 contracts), polymetallic sulfides (7 contracts), and cobalt-rich ferromanganese crusts (5 contracts). Exploration areas are located in the Clarion-Clipperton Zone, the Indian Ocean, the Mid Atlantic Ridge, the South Atlantic Ocean, and the Pacific Ocean. Potential environmental impacts of deep-sea mining include habitat alteration, sediment disturbance, plume discharge, toxic compounds release, light and noise generation, and air emissions. They could cause burial and smothering of benthic species, health problems for marine species, biodiversity loss, reduced photosynthetic mechanism, behavior change and masking acoustic communication for mammals and fish, heavy metals bioaccumulation up the food web, decrease of the content of dissolved oxygen, and climate change. An important concern related to deep-sea mining is our knowledge gap regarding deep-sea bio-communities. The ecological consequences that will be caused in the remote, unique, fragile, and little-understood deep-sea ecosystems and inhabitants are still largely unknown. The blue economy conceptualizes oceans as developing spaces supplying socio-economic benefits for current and future generations but also protecting, supporting, and restoring biodiversity and ecological productivity. In that sense, people should apply holistic management and make an assessment of marine mining impacts on ecosystem services, including the categories of provisioning, regulating, supporting, and cultural services. The variety in environmental parameters, the range in sea depth, the diversity in the characteristics of marine species, and the possible proximity to other existing maritime industries cause a span of marine mining impact the ability of ecosystems to support people and nature. In conclusion, the use of the untapped potential of the global ocean demands a liable and sustainable attitude. Moreover, there is a need to change our lifestyle and move beyond the philosophy of single-use. Living in a throw-away society based on a linear approach to resource consumption, humans are putting too much pressure on the natural environment. Applying modern, sustainable and eco-friendly approaches according to the principle of circular economy, a substantial amount of natural resource savings will be achieved. Acknowledgement: This work is part of the MAREE project, financially supported by the Division VI of IUPAC. This work has been partly supported by the University of Piraeus Research Center.

Keywords: blue economy, deep-sea mining, ecosystem services, environmental impacts

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3634 Improvement of Performance for R. C. Beams Made from Recycled Aggregate by Using Non-Traditional Admixture

Authors: A. H. Yehia, M. M. Rashwan, K. A. Assaf, K. Abd el Samee

Abstract:

The aim of this work is to use an environmental, cheap; organic non-traditional admixture to improve the structural behavior of sustainable reinforced concrete beams contains different ratios of recycled concrete aggregate. The used admixture prepared by using wastes from vegetable oil industry. Under and over reinforced concrete beams made from natural aggregate and different ratios of recycled concrete aggregate were tested under static load until failure. Eight beams were tested to investigate the performance and mechanism effect of admixture on improving deformation characteristics, modulus of elasticity and toughness of tested beams. Test results show efficiency of organic admixture on improving flexural behavior of beams contains 20% recycled concrete aggregate more over the other ratios.

Keywords: deflection, modulus of elasticity, non-traditional admixture, recycled concrete aggregate, strain, toughness, under and over reinforcement

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3633 Urban Seismic Risk Reduction in Algeria: Adaptation and Application of the RADIUS Methodology

Authors: Mehdi Boukri, Mohammed Naboussi Farsi, Mounir Naili, Omar Amellal, Mohamed Belazougui, Ahmed Mebarki, Nabila Guessoum, Brahim Mezazigh, Mounir Ait-Belkacem, Nacim Yousfi, Mohamed Bouaoud, Ikram Boukal, Aboubakr Fettar, Asma Souki

Abstract:

The seismic risk to which the urban centres are more and more exposed became a world concern. A co-operation on an international scale is necessary for an exchange of information and experiments for the prevention and the installation of action plans in the countries prone to this phenomenon. For that, the 1990s was designated as 'International Decade for Natural Disaster Reduction (IDNDR)' by the United Nations, whose interest was to promote the capacity to resist the various natural, industrial and environmental disasters. Within this framework, it was launched in 1996, the RADIUS project (Risk Assessment Tools for Diagnosis of Urban Areas Against Seismic Disaster), whose the main objective is to mitigate seismic risk in developing countries, through the development of a simple and fast methodological and operational approach, allowing to evaluate the vulnerability as well as the socio-economic losses, by probable earthquake scenarios in the exposed urban areas. In this paper, we will present the adaptation and application of this methodology to the Algerian context for the seismic risk evaluation in urban areas potentially exposed to earthquakes. This application consists to perform an earthquake scenario in the urban centre of Constantine city, located at the North-East of Algeria, which will allow the building seismic damage estimation of this city. For that, an inventory of 30706 building units was carried out by the National Earthquake Engineering Research Centre (CGS). These buildings were digitized in a data base which comprises their technical information by using a Geographical Information system (GIS), and then they were classified according to the RADIUS methodology. The study area was subdivided into 228 meshes of 500m on side and Ten (10) sectors of which each one contains a group of meshes. The results of this earthquake scenario highlights that the ratio of likely damage is about 23%. This severe damage results from the high concentration of old buildings and unfavourable soil conditions. This simulation of the probable seismic damage of the building and the GIS damage maps generated provide a predictive evaluation of the damage which can occur by a potential earthquake near to Constantine city. These theoretical forecasts are important for decision makers in order to take the adequate preventive measures and to develop suitable strategies, prevention and emergency management plans to reduce these losses. They can also help to take the adequate emergency measures in the most impacted areas in the early hours and days after an earthquake occurrence.

Keywords: seismic risk, mitigation, RADIUS, urban areas, Algeria, earthquake scenario, Constantine

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3632 Functional Ingredients from Potato By-Products: Innovative Biocatalytic Processes

Authors: Salwa Karboune, Amanda Waglay

Abstract:

Recent studies indicate that health-promoting functional ingredients and nutraceuticals can help support and improve the overall public health, which is timely given the aging of the population and the increasing cost of health care. The development of novel ‘natural’ functional ingredients is increasingly challenging. Biocatalysis offers powerful approaches to achieve this goal. Our recent research has been focusing on the development of innovative biocatalytic approaches towards the isolation of protein isolates from potato by-products and the generation of peptides. Potato is a vegetable whose high-quality proteins are underestimated. In addition to their high proportion in the essential amino acids, potato proteins possess angiotensin-converting enzyme-inhibitory potency, an ability to reduce plasma triglycerides associated with a reduced risk of atherosclerosis, and stimulate the release of the appetite regulating hormone CCK. Potato proteins have long been considered not economically feasible due to the low protein content (27% dry matter) found in tuber (Solanum tuberosum). However, potatoes rank the second largest protein supplying crop grown per hectare following wheat. Potato proteins include patatin (40-45 kDa), protease inhibitors (5-25 kDa), and various high MW proteins. Non-destructive techniques for the extraction of proteins from potato pulp and for the generation of peptides are needed in order to minimize functional losses and enhance quality. A promising approach for isolating the potato proteins was developed, which involves the use of multi-enzymatic systems containing selected glycosyl hydrolase enzymes that synergistically work to open the plant cell wall network. This enzymatic approach is advantageous due to: (1) the use of milder reaction conditions, (2) the high selectivity and specificity of enzymes, (3) the low cost and (4) the ability to market natural ingredients. Another major benefit to this enzymatic approach is the elimination of a costly purification step; indeed, these multi-enzymatic systems have the ability to isolate proteins, while fractionating them due to their specificity and selectivity with minimal proteolytic activities. The isolated proteins were used for the enzymatic generation of active peptides. In addition, they were applied into a reduced gluten cookie formulation as consumers are putting a high demand for easy ready to eat snack foods, with high nutritional quality and limited to no gluten incorporation. The addition of potato protein significantly improved the textural hardness of reduced gluten cookies, more comparable to wheat flour alone. The presentation will focus on our recent ‘proof-of principle’ results illustrating the feasibility and the efficiency of new biocatalytic processes for the production of innovative functional food ingredients, from potato by-products, whose potential health benefits are increasingly being recognized.

Keywords: biocatalytic approaches, functional ingredients, potato proteins, peptides

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3631 Public Participation and Decision-Making towards Planning Legislation: A Case for GCC Countries

Authors: Saad Saeed Althiabi

Abstract:

There is great progress in formulating and executing legislative policies in GCC, however, the public participation in formulating and in major decision making still remains weak. Drawing attention on the international law of public participation in construction and natural resource management, this paper aims in creating a feasible legislative framework for extensive public participation in the industries such as construction and oil and gas decision-making that GCC can implement. This paper would address the conflicts associated with the management and creation of legislation and ensuring public participation for the creation of a practical framework. A feasible legislative framework must take into account the various factors that shape the effectiveness of participation and the elements that promote the objectives of participation. It is premised on the ground that viewing to international prescriptions might help to reveal gaps in domestic laws, as well as alternatives to overcome them.

Keywords: legislative policies, public participation, planning legislation, GCC countries, international law

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3630 Velocity Distribution in Density Currents Flowing over Rough Beds

Authors: Reza Nasrollahpour, Mohamad Hidayat Bin Jamal, Zulhilmi Bin Ismail

Abstract:

Density currents are generated when the fluid of one density is released into another fluid with a different density. These currents occur in a variety of natural and man-made environments, and this emphasises the importance of studying them. In most practical cases, the density currents flow over the surfaces which are not plane; however, there have been limited investigations in this regard. This study uses laboratory experiments to analyse the influence of bottom roughness on the velocity distribution within these dense underflows. The currents are analysed over a plane surface and three different configurations of beam-roughened beds. The velocity profiles are collected using Acoustic Doppler Velocimetry technique, and the distribution of velocity within these currents is formulated for the tested beds. The results indicate that the empirical power and Gaussian relations can describe the velocity distribution in the inner and outer regions of the profiles, respectively. Moreover, it is found that the bottom roughness is the primary controlling parameter in the inner region.

Keywords: density currents, velocity profiles, Acoustic Doppler Velocimeter, bed roughness

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3629 Modeling of System Availability and Bayesian Analysis of Bivariate Distribution

Authors: Muhammad Farooq, Ahtasham Gul

Abstract:

To meet the desired standard, it is important to monitor and analyze different engineering processes to get desired output. The bivariate distributions got a lot of attention in recent years to describe the randomness of natural as well as artificial mechanisms. In this article, a bivariate model is constructed using two independent models developed by the nesting approach to study the effect of each component on reliability for better understanding. Further, the Bayes analysis of system availability is studied by considering prior parametric variations in the failure time and repair time distributions. Basic statistical characteristics of marginal distribution, like mean median and quantile function, are discussed. We use inverse Gamma prior to study its frequentist properties by conducting Monte Carlo Markov Chain (MCMC) sampling scheme.

Keywords: reliability, system availability Weibull, inverse Lomax, Monte Carlo Markov Chain, Bayesian

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3628 Metal-Based Deep Eutectic Solvents for Extractive Desulfurization of Fuels: Analysis from Molecular Dynamics Simulations

Authors: Aibek Kukpayev, Dhawal Shah

Abstract:

Combustion of sour fuels containing high amount of sulfur leads to the formation of sulfur oxides, which adversely harm the environment and has a negative impact on human health. Considering this, several legislations have been imposed to bring down the sulfur content in fuel to less than 10 ppm. In recent years, novel deep eutectic solvents (DESs) have been developed to achieve deep desulfurization, particularly to extract thiophenic compounds from liquid fuels. These novel DESs, considered as analogous to ionic liquids are green, eco-friendly, inexpensive, and sustainable. We herein, using molecular dynamic simulation, analyze the interactions of metal-based DESs with model oil consisting of thiophenic compounds. The DES used consists of polyethylene glycol (PEG-200) as a hydrogen bond donor, choline chloride (ChCl) or tetrabutyl ammonium chloride (TBAC) as a hydrogen bond acceptor, and cobalt chloride (CoCl₂) as metal salt. In particular, the combination of ChCl: PEG-200:CoCl₂ at a ratio 1:2:1 and the combination of TBAC:PEG-200:CoCl₂ at a ratio 1:2:0.25 were simulated, separately, with model oil consisting of octane and thiophenes at 25ᵒC and 1 bar. The results of molecular dynamics simulations were analyzed in terms of interaction energies between different components. The simulations revealed a stronger interaction between DESs/thiophenes as compared with octane/thiophenes, suggestive of an efficient desulfurization process. In addition, our analysis suggests that the choice of hydrogen bond acceptor strongly influences the efficiency of the desulfurization process. Taken together, the results also show the importance of the metal ion, although present in small amount, in the process, and the role of the polymer in desulfurization of the model fuel.

Keywords: deep eutectic solvents, desulfurization, molecular dynamics simulations, thiophenes

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3627 Automatic Speech Recognition Systems Performance Evaluation Using Word Error Rate Method

Authors: João Rato, Nuno Costa

Abstract:

The human verbal communication is a two-way process which requires a mutual understanding that will result in some considerations. This kind of communication, also called dialogue, besides the supposed human agents it can also be performed between human agents and machines. The interaction between Men and Machines, by means of a natural language, has an important role concerning the improvement of the communication between each other. Aiming at knowing the performance of some speech recognition systems, this document shows the results of the accomplished tests according to the Word Error Rate evaluation method. Besides that, it is also given a set of information linked to the systems of Man-Machine communication. After this work has been made, conclusions were drawn regarding the Speech Recognition Systems, among which it can be mentioned their poor performance concerning the voice interpretation in noisy environments.

Keywords: automatic speech recognition, man-machine conversation, speech recognition, spoken dialogue systems, word error rate

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3626 Use of Diatomite for the Elimination of Chromium Three from Wastewater Annaba, Algeria

Authors: Sabiha Chouchane, Toufik Chouchane, Azzedine Hani

Abstract:

The wastewater was treated with a natural asorbent “Diatomite” to eliminate chromium three. Diatomite is an element that comes from Sig (west of Algeria). The physicochemical characterization revealed that the diatomite is mainly made up of silica, lime and a lower degree of alumina. The process considered in static regime, at 20°C, an ion stirring speed of 150 rpm, a pH = 4 and a grain diameter of between 100 and 150µm, shows that one gram of diatomite purified can fix according to the Langmuir model up to 39.64 mg/g of chromium with pseudo 1st order kinetics. The pseudo-equilibrium time highlighted is 25 minutes. The affinity between the adsorbent and the adsorbate follows the value of the RL ratio indicates us that the solid used has a good adsorption capacity. The external transport of the metal ions from the solution to the adsorbent seems to be a step controlling the speed of the overall process. On the other hand, internal transport in the pores is not the only limiting mechanism of sorption kinetics. Thermodynamic parameters show that chromium sorption is spontaneous and exothermic with negative entropy.

Keywords: adsorption, diatomite, crIII, wastewater

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3625 Evaluation of Ficus racemosa (Moraceae) as a Potential Source for Drug Formulation Against Coccidiosis

Authors: Naveeda Akhtar Qureshi, Wajiha

Abstract:

Coccidiosis is a protozoan parasitic disease of genus Eimeria. It is an avian infection causing a great economic loss of 3 billion USD per year globally. A number of anticoccidial drugs are in use however many of them have side effects and cost effective. With increase in poultry demand throughout the world there is a need of more drugs and vaccines against coccidiosis. The present study is based upon the use of F. racemosa a medicinal plant to be a potential source of anticoccidial agents. The methanolic leaves extract was fractionated by column and thin layer chromatography and got nineteen fractions. Each fraction different concentrations was evaluated for its anticoccidial properties in an invitro experiment against E. tenella, E. necatrix and E. mitis. The anticoccidial active fractions were further characterized by spectroscopy (UV-Vis, FTIR) and GC-MS analysis. The in silico molecular docking of active fractions identified compounds were carried out. Among all fractions significantly maximum sporulation inhibition efficacy was shown by F-19 (67.11±2.18) followed by F-15 (65.21±1.34) at concentration of 30mg/ml against E. tenella. The significantly highest sporozoites viability inhibition was shown by F-19 (69.23±2.11) followed by F-15 (67.14±1.52) against E. necatrix at concentration 30mg/ml. Anticoccidial active fractions 15 and 19 showed peak spectrum at 207 and 202nm respectively by UV analysis. Their FTIR analysis confirmed the presence of carboxylic acid, amines, phenols, etc. Anticoccidial active compounds like Cyclododecane methanol, oleic acid, Octadecanoic acid, etc were identified by GC-MS analysis. Identified compounds in silico molecular docking study showed that cyclododecane methanol of F-19 and oleic acid of F-15 showed highest binding affinity with target S-Adenosylmethionine synthase. Hence for further authentication in vivo anticoccidial studies are recommended.

Keywords: ficus racemosa, cluster fig, column chromatography, anticoccidial fractions, GC-MS, molecular docking., s-adenosylmethionine synthase

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3624 Ankaferd Blood Stopper (ABS) Has Protective Effect on Colonic Inflammation: An in Vitro Study in Raw 264.7 and Caco-2 Cells

Authors: Aysegul Alyamac, Sukru Gulec

Abstract:

Ankaferd Blood Stopper (ABS) is a plant extract used to stop bleeding caused by injuries and surgical interventions. ABS also involved in wound healing of intestinal mucosal damage due to oxidative stress and inflammation. Inflammatory Bowel Disease (IBD) is a common chronic disorder of the gastrointestinal tract that causes abdominal pain, diarrhea, and gastrointestinal bleeding, and increases the risk of colon cancer. Inflammation is an essential factor in the development of IBD. The various studies have been performed about the physiological effects of ABS; however, ABS dependent mechanism on colonic inflammation has not been elucidated. Thus, the protective effect of ABS on colonic inflammation was investigated in this study. The Caco-2 and RAW 264.7 murine macrophage cells were used as a model of in vitro colonic inflammation. RAW 264.7 cells were treated with lipopolysaccharide (LPS) for 12 hours to induce the inflammation, and a conditional medium was obtained. Caco-2 cells were treated with 15 µl/ml ABS for 4 hours, then incubated with conditional medium and the cells also were incubated with 15 µl/ml ABS and conditional medium together for 4 hours. Tumor necrosis factor alpha (TNF-α) protein levels were targeted in testing inflammatory condition and its level was significantly increased (25 fold, p<0.001) compared to the control group by using Enzyme-Linked Immunosorbent Assay (ELISA) method. The COX-2 mRNA level was used as a marker gene to show the possible anti-inflammatory effect of ABS in Caco-2 cells. RAW cells-derived conditional medium significantly (3.3 fold, p<0.001) induced cyclooxygenase-2 (COX-2) mRNA levels in Caco-2 cells. The pretreatment of Caco-2 cells caused a significant decrease (3.3 fold, p<0.001) in COX-2 mRNA levels relative to conditional medium given group. Furthermore, COX-2 mRNA level was significantly reduced (4,7 fold, p<0.001) in ABS and conditional medium treated group. These results suggest that ABS might have an anti-inflammatory effect in vitro.

Keywords: Ankaferd blood stopper, CaCo-2, colonic inflammation, RAW 264.7

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3623 Contextual Toxicity Detection with Data Augmentation

Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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3622 Prediction and Identification of a Permissive Epitope Insertion Site for St Toxoid in cfaB from Enterotoxigenic Escherichia coli

Authors: N. Zeinalzadeh, Mahdi Sadeghi

Abstract:

Enterotoxigenic Escherichia coli (ETEC) is the most common cause of non-inflammatory diarrhea in the developing countries, resulting in approximately 20% of all diarrheal episodes in children in these areas. ST is one of the most important virulence factors and CFA/I is one of the frequent colonization factors that help to process of ETEC infection. ST and CfaB (CFA/I subunit) are among vaccine candidates against ETEC. So, ST because of its small size is not a good immunogenic in the natural form. However to increase its immunogenic potential, here we explored candidate positions for ST insertion in CfaB sequence. After bioinformatics analysis, one of the candidate positions was selected and the chimeric gene (cfaB*st) sequence was synthesized and expressed in E. coli BL21 (DE3). The chimeric recombinant protein was purified with Ni-NTA columns and characterized with western blot analysis. The residue 74-75 of CfaB sequence could be a good candidate position for ST and other epitopes insertion.

Keywords: bioinformatics, CFA/I, enterotoxigenic E. coli, ST toxoid

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3621 Batman Forever: The Economics of Overlapping Rights

Authors: Franziska Kaiser, Alexander Cuntz

Abstract:

When copyrighted comic characters are also protected under trademark laws, intellectual property (IP) rights can overlap. Arguably, registering a trademark can increase transaction costs for cross-media uses of characters, or it can favor advertise across a number of sales channels. In an application to book, movie, and video game publishing industries, we thus ask how creative reuse is affected in situations of overlapping rights and whether ‘fuzzy boundaries’ of right frameworks are, in fact, enhancing or decreasing content sales. We use a major U.S. Supreme Court decision as a quasi-natural experiment to apply an IV estimation in our analysis. We find that overlapping rights frameworks negatively affect creative reuses. At large, when copyright-protected comic characters are additionally registered as U.S. trademarks, they are less often reprinted and enter fewer video game productions while generating less revenue from game sales.

Keywords: copyright, fictional characters, trademark, reuse

Procedia PDF Downloads 202
3620 The Effect of Biochar, Inoculated Biochar and Compost Biological Component of the Soil

Authors: Helena Dvořáčková, Mikajlo Irina, Záhora Jaroslav, Elbl Jakub

Abstract:

Biochar can be produced from the waste matter and its application has been associated with returning of carbon in large amounts into the soil. The impacts of this material on physical and chemical properties of soil have been described. The biggest part of the research work is dedicated to the hypothesis of this material’s toxic effects on the soil life regarding its effect on the soil biological component. At present, it has been worked on methods which could eliminate these undesirable properties of biochar. One of the possibilities is to mix biochar with organic material, such as compost, or focusing on the natural processes acceleration in the soil. In the experiment has been used as the addition of compost as well as the elimination of toxic substances by promoting microbial activity in aerated water environment. Biochar was aerated for 7 days in a container with a volume of 20 l. This way modified biochar had six times higher biomass production and reduce mineral nitrogen leaching. Better results have been achieved by mixing biochar with compost.

Keywords: leaching of nitrogen, soil, biochar, compost

Procedia PDF Downloads 321
3619 Magnetic Nano-Composite of Self-Doped Polyaniline Nanofibers for Magnetic Dispersive Micro Solid Phase Extraction Applications

Authors: Hatem I. Mokhtar, Randa A. Abd-El-Salam, Ghada M. Hadad

Abstract:

An improved nano-composite of self-doped polyaniline nanofibers and silica-coated magnetite nanoparticles were prepared and evaluated for suitability to magnetic dispersive micro solid-phase extraction. The work focused on optimization of the composite capacity to extract four fluoroquinolones (FQs) antibiotics, ciprofloxacin, enrofloxacin, danofloxacin, and difloxacin from water and improvement of composite stability towards acid and atmospheric degradation. Self-doped polyaniline nanofibers were prepared by oxidative co-polymerization of aniline with anthranilic acid. Magnetite nanopariticles were prepared by alkaline co-precipitation and coated with silica by silicate hydrolysis on magnetite nanoparticles surface at pH 6.5. The composite was formed by self-assembly by mixing self-doped polyaniline nanofibers with silica-coated magnetite nanoparticles dispersions in ethanol. The composite structure was confirmed by transmission electron microscopy (TEM). Self-doped polyaniline nanofibers and magnetite chemical structures were confirmed by FT-IR while silica coating of the magnetite was confirmed by Energy Dispersion X-ray Spectroscopy (EDS). Improved stability of the composite magnetic component was evidenced by resistance to degrade in 2N HCl solution. The adsorption capacity of self-doped polyaniline nanofibers based composite was higher than previously reported corresponding composite prepared from polyaniline nanofibers instead of self-doped polyaniline nanofibers. Adsorption-pH profile for the studied FQs on the prepared composite revealed that the best pH for adsorption was in range of 6.5 to 7. Best extraction recovery values were obtained at pH 7 using phosphate buffer. The best solvent for FQs desorption was found to be 0.1N HCl in methanol:water (8:2; v/v) mixture. 20 mL of Spiked water sample with studied FQs were preconcentrated using 4.8 mg of composite and resulting extracts were analysed by HPLC-UV method. The prepared composite represented a suitable adsorbent phase for magnetic dispersive micro-solid phase application.

Keywords: fluoroquinolones, magnetic dispersive micro extraction, nano-composite, self-doped polyaniline nanofibers

Procedia PDF Downloads 117
3618 Mapping of Potential Areas for Groundwater Storage in the Sais Plateau and Its Middle Atlas Borders, Morocco

Authors: Abdelghani Qadem, Zohair Qadem, Mohamed Lasri

Abstract:

At the level of the Moroccan Sais Plateau, groundwater constitutes strategic natural resources for agricultural, industrial, and domestic use. Today, due to climate change and population growth, the pressure on groundwater has increased considerably. This contribution aims to delineate and map potential areas for groundwater storage in the area in question using GIS and remote sensing. The methodology adopted is based on the identification of the thematic layers used to assess the potential recharge of the aquifer. The mapping of potential areas for groundwater storage is developed through the method of modeling and weighted overlay using the spatial analysis tool on the Geographic Information System. The results obtained can be used for the planning of future artificial recharge projects in the study area in order to ensure the good sustainable use of this underground gift.

Keywords: Morocco, climate change, groundwater, mapping, recharge

Procedia PDF Downloads 76
3617 Ecology in Politics: A Multimodal Eco-Critical Analysis of Environmental Discourse

Authors: Amany ElShazly, Lubna A. Sherif

Abstract:

The entanglement of humans with the environment has always been inevitable and often causes destruction. In this respect, ‘Ecolinguistics’ helps humans to understand the link between languages and the environment. Stibbe (2014a) has indicated that ‘linguistics’, particularly, Critical Discourse Studies (CDS), provides an interpretation of language which shapes world views, while the ‘eco’ side maintains the life-sustaining interactions of humans and the physical environment. This paper considers two key ecological instances, namely: The Grand Ethiopian Renaissance Dam (GERD) as a focal point of political dispute and THE LINE project as well as Etthadar lel Akhdar (Go Green Initiative) as two examples of combating ecological degradation. ‘Ecosophy’ as explained by Naess (1996) is used to describe the ecolinguistic framework, which assesses discourse where the linguistic lens focuses on the use of metaphor, and ‘Positive Discourse’ framework, which resonates with respect and care for the natural world.

Keywords: ecosophy, critical discourse studies, metaphor, positive discourse, social semiotics, ecolinguistics

Procedia PDF Downloads 88
3616 Evaluation of Modern Natural Language Processing Techniques via Measuring a Company's Public Perception

Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

Abstract:

Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

Procedia PDF Downloads 136
3615 Analysis of a IncResU-Net Model for R-Peak Detection in ECG Signals

Authors: Beatriz Lafuente Alcázar, Yash Wani, Amit J. Nimunkar

Abstract:

Cardiovascular Diseases (CVDs) are the leading cause of death globally, and around 80% of sudden cardiac deaths are due to arrhythmias or irregular heartbeats. The majority of these pathologies are revealed by either short-term or long-term alterations in the electrocardiogram (ECG) morphology. The ECG is the main diagnostic tool in cardiology. It is a non-invasive, pain free procedure that measures the heart’s electrical activity and that allows the detecting of abnormal rhythms and underlying conditions. A cardiologist can diagnose a wide range of pathologies based on ECG’s form alterations, but the human interpretation is subjective and it is contingent to error. Moreover, ECG records can be quite prolonged in time, which can further complicate visual diagnosis, and deeply retard disease detection. In this context, deep learning methods have risen as a promising strategy to extract relevant features and eliminate individual subjectivity in ECG analysis. They facilitate the computation of large sets of data and can provide early and precise diagnoses. Therefore, the cardiology field is one of the areas that can most benefit from the implementation of deep learning algorithms. In the present study, a deep learning algorithm is trained following a novel approach, using a combination of different databases as the training set. The goal of the algorithm is to achieve the detection of R-peaks in ECG signals. Its performance is further evaluated in ECG signals with different origins and features to test the model’s ability to generalize its outcomes. Performance of the model for detection of R-peaks for clean and noisy ECGs is presented. The model is able to detect R-peaks in the presence of various types of noise, and when presented with data, it has not been trained. It is expected that this approach will increase the effectiveness and capacity of cardiologists to detect divergences in the normal cardiac activity of their patients.

Keywords: arrhythmia, deep learning, electrocardiogram, machine learning, R-peaks

Procedia PDF Downloads 175
3614 Modified 'Perturb and Observe' with 'Incremental Conductance' Algorithm for Maximum Power Point Tracking

Authors: H. Fuad Usman, M. Rafay Khan Sial, Shahzaib Hamid

Abstract:

The trend of renewable energy resources has been amplified due to global warming and other environmental related complications in the 21st century. Recent research has very much emphasized on the generation of electrical power through renewable resources like solar, wind, hydro, geothermal, etc. The use of the photovoltaic cell has become very public as it is very useful for the domestic and commercial purpose overall the world. Although a single cell gives the low voltage output but connecting a number of cells in a series formed a complete module of the photovoltaic cells, it is becoming a financial investment as the use of it fetching popular. This also reduced the prices of the photovoltaic cell which gives the customers a confident of using this source for their electrical use. Photovoltaic cell gives the MPPT at single specific point of operation at a given temperature and level of solar intensity received at a given surface whereas the focal point changes over a large range depending upon the manufacturing factor, temperature conditions, intensity for insolation, instantaneous conditions for shading and aging factor for the photovoltaic cells. Two improved algorithms have been proposed in this article for the MPPT. The widely used algorithms are the ‘Incremental Conductance’ and ‘Perturb and Observe’ algorithms. To extract the maximum power from the source to the load, the duty cycle of the convertor will be effectively controlled. After assessing the previous techniques, this paper presents the improved and reformed idea of harvesting maximum power point from the photovoltaic cells. A thoroughly go through of the previous ideas has been observed before constructing the improvement in the traditional technique of MPP. Each technique has its own importance and boundaries at various weather conditions. An improved technique of implementing the use of both ‘Perturb and Observe’ and ‘Incremental Conductance’ is introduced.

Keywords: duty cycle, MPPT (Maximum Power Point Tracking), perturb and observe (P&O), photovoltaic module

Procedia PDF Downloads 171
3613 The Traffic Congestion in Biskra in Algeria

Authors: Selatnia Khaled Grine Ikram

Abstract:

The city of Biskra, like other Algerian cities, knows of urban traffic congestion. The concentration of investments especially in the secondary and tertiary sectors in the Wilaya has attracted a large rural population. The latter, combined with the high rate of natural growing, favored the imbalance of the spatial frame of wilayal system and consequently the traffic congestion of the primate city (Biskra). This urban disease is explained by a two-tier development. The capital of Wilaya growing faster than its others centers body and takes measurements of proportion to the whole. The consequences can only be negative. The pressure on the roads, the growth of the fleet, overloading of equipment and activities have become the characteristics of the city of Biskra, which can no longer meet the needs of its inhabitants. This research attempts to show the relationship between urban congestion of the primate city and the imbalance of the spatial structure of the micro-regional urban system.

Keywords: traffic congestion, spatial structure, pressure on the roads, equipment and activities

Procedia PDF Downloads 673
3612 Design Patterns for Emergency Management Processes

Authors: Tomáš Ludík, Jiří Barta, Josef Navrátil

Abstract:

Natural or human made disasters have a significant negative impact on the environment. At the same time there is an extensive effort to support management and decision making in emergency situations by information technologies. Therefore the purpose of the paper is to propose a design patterns applicable in emergency management, enabling better analysis and design of emergency management processes and therefore easier development and deployment of information systems in the field of emergency management. It will be achieved by detailed analysis of existing emergency management legislation, contingency plans, and information systems. The result is a set of design patterns focused at emergency management processes that enable easier design of emergency plans or development of new information system. These results will have a major impact on the development of new information systems as well as to more effective and faster solving of emergencies.

Keywords: analysis and design, Business Process Modelling Notation, contingency plans, design patterns, emergency management

Procedia PDF Downloads 480