Search results for: resonant two-photon ionization time of flight mass spectrometry (2C-R2PI)
16475 Intrarenal Injection of Pentobarbital Sodium for Euthanasia in Cats: 131 Cases, 2010-2011
Authors: Kathleen Cooney, Jennifer Coates, Lesley Leach, Kristin Hrenchir
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The objective of this retrospective study was to determine whether intrarenal injection of pentobarbital sodium is a practicable method of euthanasia in client-owned cats. 131 Cats were anesthetized using a combination of tiletamine, zolazepam, and acepromazine given by of subcutaneous or intramuscular injection. Once an appropriate plane of anesthesia was reached, 6 ml of pentobarbital sodium was injected into either the left or right kidney. The patient’s age, sex, estimated weight, presenting condition, estimated dehydration level, palpable characteristics of the kidney pre and post injection, physical response of the cat, and time to cardiopulmonary arrest were recorded. Analysis of 131 records revealed that cats receiving an intrarenal injection of pentobarbital sodium had an average time to cardiopulmonary arrest of 1 minute. The great majority (79%) experienced cardiopulmonary arrest in less than one minute with the remainder experiencing cardiopulmonary arrest between 1 and 8 minutes of the injection. 95% of cats had no observable reaction to intrarenal injection other than cardiopulmonary arrest. In the 19% of cases where kidney swelling was not palpable upon injection, average time to cardiopulmonary arrest increased from 0.9 to 1.6 min. Conclusions and Clinical Relevance: Intrarenal injections of pentobarbital sodium are similar in effect to intravenous methods of euthanasia. Veterinarians who elect to use intrarenal injections can expect cardiopulmonary arrest to occur quickly in the majority of patients with few agonal reactions. Intrarenal injection of pentobarbital sodium in anesthetized cats has ideally suited for cases of owner observed euthanasia when obtaining intravenous access would difficult or disruptive.Keywords: euthanasia, injection, intrarenal, pentobarbital sodium
Procedia PDF Downloads 33816474 Kinetic Rate Comparison of Methane Catalytic Combustion of Palladium Catalysts Impregnated onto ɤ-Alumina and Bio-Char
Authors: Noor S. Nasri, Eric C. A. Tatt, Usman D. Hamza, Jibril Mohammed, Husna M. Zain
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Climate change has becoming a global environmental issue that may trigger irreversible changes in the environment with catastrophic consequences for human, animals and plants on our planet. Methane, carbon dioxide and nitrous oxide are the greenhouse gases (GHG) and as the main factor that significantly contributes to the global warming. Mainly carbon dioxide be produced and released to atmosphere by thermal industrial and power generation sectors. Methane is dominant component of natural gas releases significant of thermal heat, and the gaseous pollutants when homogeneous thermal combustion takes place at high temperature. Heterogeneous catalytic Combustion (HCC) principle is promising technologies towards environmental friendly energy production should be developed to ensure higher yields with lower pollutants gaseous emissions and perform complete combustion oxidation at moderate temperature condition as comparing to homogeneous high thermal combustion. Hence the principle has become a very interesting alternative total oxidation for the treatment of pollutants gaseous emission especially NOX product formation. Noble metals are dispersed on a support-porous HCC such as γ- Al2O3, TiO2 and ThO2 to increase thermal stability of catalyst and to increase to effectiveness of catalytic combustion. Support-porous HCC material to be selected based on factors of the surface area, porosity, thermal stability, thermal conductivity, reactivity with reactants or products, chemical stability, catalytic activity, and catalyst life. γ- Al2O3 with high catalytic activity and can last longer life of catalyst, is commonly used as the support for Pd catalyst at low temperatures. Sustainable and renewable support-material of bio-mass char was derived from agro-industrial waste material and used to compare with those the conventional support-porous material. The abundant of biomass wastes generated in palm oil industries is one potential source to convert the wastes into sustainable material as replacement of support material for catalysts. Objective of this study was to compare the kinetic rate of reaction the combustion of methane on Palladium (Pd) based catalyst with Al2O3 support and bio-char (Bc) support derived from shell kernel. The 2wt% Pd was prepared using incipient wetness impregnation method and the HCC performance was accomplished using tubular quartz reactor with gas mixture ratio of 3% methane and 97% air. Material characterization was determined using TGA, SEM, and BET surface area. The methane porous-HCC conversion was carried out by online gas analyzer connected to the reactor that performed porous-HCC. BET surface area for prepared 2 wt% Pd/Bc is smaller than prepared 2wt% Pd/ Al2O3 due to its low porosity between particles. The order of catalyst activity based on kinetic rate on reaction of catalysts in low temperature is prepared 2wt% Pd/Bc > calcined 2wt% Pd/ Al2O3 > prepared 2wt% Pd/ Al2O3 > calcined 2wt% Pd/Bc. Hence the usage of agro-industrial bio-mass waste material can enhance the sustainability principle.Keywords: catalytic-combustion, environmental, support-bio-char material, sustainable and renewable material
Procedia PDF Downloads 38516473 Cubic Trigonometric B-Spline Approach to Numerical Solution of Wave Equation
Authors: Shazalina Mat Zin, Ahmad Abd. Majid, Ahmad Izani Md. Ismail, Muhammad Abbas
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The generalized wave equation models various problems in sciences and engineering. In this paper, a new three-time level implicit approach based on cubic trigonometric B-spline for the approximate solution of wave equation is developed. The usual finite difference approach is used to discretize the time derivative while cubic trigonometric B-spline is applied as an interpolating function in the space dimension. Von Neumann stability analysis is used to analyze the proposed method. Two problems are discussed to exhibit the feasibility and capability of the method. The absolute errors and maximum error are computed to assess the performance of the proposed method. The results were found to be in good agreement with known solutions and with existing schemes in literature.Keywords: collocation method, cubic trigonometric B-spline, finite difference, wave equation
Procedia PDF Downloads 53216472 Power of Doubling: Population Growth and Resource Consumption
Authors: Sarika Bahadure
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Sustainability starts with conserving resources for future generations. Since human’s existence on this earth, he has been consuming natural resources. The resource consumption pace in the past was very slow, but industrialization in 18th century brought a change in the human lifestyle. New inventions and discoveries upgraded the human workforce to machines. The mass manufacture of goods provided easy access to products. In the last few decades, the globalization and change in technologies brought consumer oriented market. The consumption of resources has increased at a very high scale. This overconsumption pattern brought economic boom and provided multiple opportunities, but it also put stress on the natural resources. This paper tries to put forth the facts and figures of the population growth and consumption of resources with examples. This is explained with the help of the mathematical expression of doubling known as exponential growth. It compares the carrying capacity of the earth and resource consumption of humans’ i.e. ecological footprint and bio-capacity. Further, it presents the need to conserve natural resources and re-examine sustainable resource use approach for sustainability.Keywords: consumption, exponential growth, population, resources, sustainability
Procedia PDF Downloads 22516471 The Effects of Distribution Channels on the Selling Prices of Hotels in Time of Crisis
Authors: Y. Yılmaz, C. Ünal, A. Dursun
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Distribution channels play significant role for hotels. Direct and indirect selling options of hotel rooms have been increased especially with the help of new technologies, i.e. hotel’s own web sites and online booking sites. Although these options emerged as tools for diversifying the distribution channels, vast number of hotels -mostly resort hotels- is still heavily dependent upon international tour operators when selling their products. On the other hand, hotel sector is so vulnerable against crises. Economic, political or any other crisis can affect hotels very badly and so it is critical to have the right balance of distribution channel to avoid the adverse impacts of a crisis. In this study, it is aimed to search the impacts of a general crisis on the selling prices of hotels which have different weights of distribution channels. The study was done in Turkey where various crises occurred in 2015 and 2016 which had great negative impacts on Turkish tourism and led enormous occupancy rate and selling price reductions. 112 upscale resort hotel in Antalya, which is the most popular tourism destination of Turkey, joined to the research. According to the results, hotels with high dependency to international tour operators are more forced to reduce their room prices in crisis time compared to the ones which use their own web sites more. It was also found that the decline in room prices is limited for hotels which are working with national tour operators and travel agencies in crisis time.Keywords: marketing channels, crisis, hotel, international tour operators, online travel agencies
Procedia PDF Downloads 31116470 Novel Framework for MIMO-Enhanced Robust Selection of Critical Control Factors in Auto Plastic Injection Moulding Quality Optimization
Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari
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Apparent quality defects such as warpage, shrinkage, weld line, etc. are such an irresistible phenomenon in mass production of auto plastic appearance parts. These frequently occurred manufacturing defects should be satisfied concurrently so as to achieve a final product with acceptable quality standards. Determining the significant control factors that simultaneously affect multiple quality characteristics can significantly improve the optimization results by eliminating the deviating effect of the so-called ineffective outliers. Hence, a robust quantitative approach needs to be developed upon which major control factors and their level can be effectively determined to help improve the reliability of the optimal processing parameter design. Hence, the primary objective of current study was to develop a systematic methodology for selection of significant control factors (SCF) relevant to multiple quality optimization of auto plastic appearance part. Auto bumper was used as a specimen with the most identical quality and production characteristics to APAP group. A preliminary failure modes and effect analysis (FMEA) was conducted to nominate a database of pseudo significant significant control factors prior to the optimization phase. Later, CAE simulation Moldflow analysis was implemented to manipulate four rampant plastic injection quality defects concerned with APAP group including warpage deflection, volumetric shrinkage, sink mark and weld line. Furthermore, a step-backward elimination searching method (SESME) has been developed for systematic pre-optimization selection of SCF based on hierarchical orthogonal array design and priority-based one-way analysis of variance (ANOVA). The development of robust parameter design in the second phase was based on DOE module powered by Minitab v.16 statistical software. Based on the F-test (F 0.05, 2, 14) one-way ANOVA results, it was concluded that for warpage deflection, material mixture percentage was the most significant control factor yielding a 58.34% of contribution while for the other three quality defects, melt temperature was the most significant control factor with a 25.32%, 84.25%, and 34.57% contribution for sin mark, shrinkage and weld line strength control. Also, the results on the he least significant control factors meaningfully revealed injection fill time as the least significant factor for both warpage and sink mark with respective 1.69% and 6.12% contribution. On the other hand, for shrinkage and weld line defects, the least significant control factors were holding pressure and mold temperature with a 0.23% and 4.05% overall contribution accordingly.Keywords: plastic injection moulding, quality optimization, FMEA, ANOVA, SESME, APAP
Procedia PDF Downloads 34216469 Post-Disaster Recovery and Impacts on Construction Resources: Case Studies of Queensland Catastrophic Events
Authors: Scott A. Abbott
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This paper examines the increase in the occurrence of natural disasters worldwide and the need to support vulnerable communities in post-disaster recovery. Preparation and implementation of post-disaster recovery projects need to be improved to allow communities to recover infrastructure, housing, economically and socially following a catastrophe. With the continual rise in catastrophic events worldwide due to climate change, impacts on construction resources affect the ability for post-disaster recovery to be undertaken. This research focuses on case studies of catastrophic events in Queensland, Australia, to contribute to the body of knowledge and gain valuable insights on lessons learned from past events and how they have been managed. The aim of this research is to adopt qualitative data using semi-structured interviews from participants predominantly from the insurance sector to understand barriers that have previously and currently exist in post-disaster recovery. Existing literature was reviewed to reveal gaps in knowledge that needed to be tested. Qualitative data was collected and summarised from field research with the results analysed and discussed. Barriers that impacted post-disaster recovery included time, cost, and resource capability and capacity. Causal themes that impacted time and cost were identified as decision making, pre-planning, and preparedness, as well as effective communication across stakeholders. The research study applied a qualitative approach to the existing literature and case studies across Queensland, Australia, to identify existing and new barriers that impact post-disaster recovery. It was recommended to implement effective procurement strategies to assist in cost control; implement pre-planning and preparedness strategies across funder, contractor, and local governments; more effective and timely decision making to reduce time and cost impacts.Keywords: construction recovery, cost, disaster recovery, resources, time
Procedia PDF Downloads 12216468 Recent Development of Materials for Proton Exchange Membrane Fuel Cell (PEMFC)
Authors: Mohammed Jourdani, Hamid Mounir, Abdellatif El Marjani
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Proton exchange membrane fuel cells (PEMFCs) have been developed as a promising power source for transportation and stationary applications, and power devices for computers and mobile telephones. This paper discusses and summarizes the latest developments of materials and remaining challenges of PEMFC. The different contributions to the material of all components and the efficiencies are analyzed. Many technical advances are introduced to increase the PEMFC fuel cell efficiency and life time for transportation, stationary and portable utilization. By the last years the total cost of this system is decreasing. However, the remaining challenges that need to be overcome mean that it will be several years before full commercialization can take place.Keywords: PEMFC fuel cell, materials, recent development, efficiency, life time, commercialization possibility
Procedia PDF Downloads 30116467 Predicting Provider Service Time in Outpatient Clinics Using Artificial Intelligence-Based Models
Authors: Haya Salah, Srinivas Sharan
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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time
Procedia PDF Downloads 11816466 A Real-Time Snore Detector Using Neural Networks and Selected Sound Features
Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis
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Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks
Procedia PDF Downloads 20216465 Forecasting Issues in Energy Markets within a Reg-ARIMA Framework
Authors: Ilaria Lucrezia Amerise
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Electricity markets throughout the world have undergone substantial changes. Accurate, reliable, clear and comprehensible modeling and forecasting of different variables (loads and prices in the first instance) have achieved increasing importance. In this paper, we describe the actual state of the art focusing on reg-SARMA methods, which have proven to be flexible enough to accommodate the electricity price/load behavior satisfactory. More specifically, we will discuss: 1) The dichotomy between point and interval forecasts; 2) The difficult choice between stochastic (e.g. climatic variation) and non-deterministic predictors (e.g. calendar variables); 3) The confrontation between modelling a single aggregate time series or creating separated and potentially different models of sub-series. The noteworthy point that we would like to make it emerge is that prices and loads require different approaches that appear irreconcilable even though must be made reconcilable for the interests and activities of energy companies.Keywords: interval forecasts, time series, electricity prices, reg-SARIMA methods
Procedia PDF Downloads 12616464 Combined Effect of Heat Stimulation and Delay Addition of Superplasticizer with Slag on Fresh and Hardened Property of Mortar
Authors: Antoni Wibowo, Harry Pujianto, Dewi Retno Sari Saputro
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The stock market can provide huge profits in a relatively short time in financial sector; however, it also has a high risk for investors and traders if they are not careful to look the factors that affect the stock market. Therefore, they should give attention to the dynamic fluctuations and movements of the stock market to optimize profits from their investment. In this paper, we present a nonlinear autoregressive exogenous model (NARX) to predict the movements of stock market; especially, the movements of the closing price index. As case study, we consider to predict the movement of the closing price in Indonesia composite index (IHSG) and choose the best structures of NARX for IHSG’s prediction.Keywords: NARX (Nonlinear Autoregressive Exogenous Model), prediction, stock market, time series
Procedia PDF Downloads 23616463 Athlete Coping: Personality Dimensions of Recovery from Injury
Authors: Randall E. Osborne, Seth A. Doty
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As participation in organized sports increases, so does the risk of sustaining an athletic injury. These unfortunate injuries result in missed time from practice and, inevitably, the field of competition. Recovery time plays a pivotal role in the overall rehabilitation of the athlete. With time and rehabilitation, an athlete’s physical injury can be properly treated. However, there seem to be few measures assessing psychological recovery from injury. Although an athlete has been cleared to return to play, there may still be lingering doubt about their injury. Overall, there is a vast difference between being physically cleared to play and being psychologically ready to return to play. Certain personality traits might serve as predictors of an individual’s rate of psychological recovery from an injury. The purpose of this research study is to explore the correlations between athletes’ personality and their recovery from an athletic injury, specifically, examining how locus of control has been utilized through other studies and can be beneficial to the current study. Additionally, this section will examine the link between hardiness and coping strategies. In the current study, mental toughness is being tested, but it is important to determine the link between these two concepts. Hardiness and coping strategies are closely related and can play a major role in an athlete’s mental toughness. It is important to examine competitive trait anxiety to illustrate perceived anxiety during athletic competition. The Big 5 and Social Support will also be examined in conjunction with recovery from athletic injury. Athletic injury is a devastating and common occurrence that can happen in any sport. Injured athletes often require resources and treatment to be able to return to the field of play. Athletes become more involved with physical and mental treatment as the length of recovery time increases. It is very reasonable to assume that personality traits would be predictive of athlete recovery from injury. The current study investigated the potential relationship between personality traits and recovery time; more specifically, the personality traits of locus of control, hardiness, social support, competitive trait anxiety, and the “Big 5” personality traits. Results indicated that athletes with a higher internal locus of control tend to report being physically ready to return to play and “ready” to return to play faster than those with an external locus of control. Additionally, Openness to Experience (among the Big 5 personality dimensions) was also related to the speed of return to play.Keywords: athlete, injury, personality, readiness to play, recovery
Procedia PDF Downloads 13416462 Theoretical Research for Influence of Irradiation on Transient Creep of Metals
Authors: Pavlo Selyshchev, Tetiana Didenko
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Via formalism of the Complex systems and in the framework of the climb - glide model a theoretical approach to describe the influence of irradiation on transient creep of metals. We consider metal under such stress and conditions of irradiation at which creep is determined by dislocation motion that consists in climb and glide. It is shown that there are qualitatively different regimes of a creep as a result of irradiation. Simulation and analysis of this phenomenon are performed. The time dependence of creep rate of metal under an irradiation is theoretically obtained. The conditions of zero minimums of the creep-rate existence as well as the times of their appearance are determined. The changing of the position of creep-rate dips in the conditions of the temperature exposure change is investigated. The obtained results are compared with the experimentally observed dependence of the creep rate on time.Keywords: creep, climb and glide of dislocations, irradiation, non-linear feed-back, point defects
Procedia PDF Downloads 19316461 Review on Green Synthesis of Gold Nanoparticles
Authors: Shabnam, Jagdeep Kumar
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Because of the impact of their greater surface area and smaller quantum sizes in comparison with other metal atoms or bulk metals, metal nanoparticles, such as those formed of gold, exhibit a variety of unusual chemical and physical properties. The size- and shape-dependent properties of gold nanoparticles (GNPs) are particularly notable. Metal nanoparticles have received a lot of attention due to their unique properties and exciting prospective uses in photonics, electronics, biological sensing, and imaging. The latest developments in GNP synthesis are discussed in this review. Green chemistry measures were used to assess the production of gold nanoparticles, with a focus on Process Mass Intensity (PMI). Based on these measurements, opportunities for improving synthetic approaches were found. With PMIs that were often in the thousands, solvent usage was found to be the main obstacle for nanoparticle synthesis, even ones that were otherwise considered to be environmentally friendly. Since ligated metal nanoparticles are the most industrially relevant but least environmentally friendly, their synthesis by arrested precipitation was chosen as the best chance for significant advances. Gold nanoparticles of small sizes and bio-stability are produced biochemically, and they are used in many biological applications.Keywords: gold, nanoparticles, green synthesis, AuNP
Procedia PDF Downloads 7816460 Dimensioning of a Solar Dryer with Application of an Experiment Design Method for Drying Food Products
Authors: B. Touati, A. Saad, B. Lips, A. Abdenbi, M. Mokhtari.
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The purpose of this study is an application of experiment design method for dimensioning of a solar drying system. NIMROD software was used to build up the matrix of experiments and to analyze the results. The software has the advantages of being easy to use and consists of a forced way, with some choices about the number and range of variation of the parameters, and the desired polynomial shape. The first design of experiments performed concern the drying with constant input characteristics of the hot air in the dryer and a second design of experiments in which the drying chamber is coupled with a solar collector. The first design of experiments allows us to study the influence of various parameters and get the studied answers in a polynomial form. The correspondence between the polynomial thus determined, and the model results were good. The results of the polynomials of the second design of experiments and those of the model are worse than the results in the case of drying with constant input conditions. This is due to the strong link between all the input parameters, especially, the surface of the sensor and the drying chamber, and the mass of the product.Keywords: solar drying, experiment design method, NIMROD, mint leaves
Procedia PDF Downloads 49716459 Triplex Detection of Pistacia vera, Arachis hypogaea and Pisum sativum in Processed Food Products Using Probe Based PCR
Authors: Ergün Şakalar, Şeyma Özçirak Ergün, Emrah Yalazi̇, Emine Altinkaya, Cengiz Ataşoğlu
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In recent years, food allergies which cause serious health problems affect to public health around the world. Foodstuffs which contain allergens are either intentionally used as ingredients or are encased as contaminant in food products. The prevalence of clinical allergy to peanuts and nuts is estimated at about 0.4%-1.1% of the adult population, representing the allergy to pistachio the 7% of the cases of tree nut causing allergic reactions. In order to protect public health and enforce the legislation, methods for sensitive analysis of pistachio and peanut contents in food are required. Pea, pistachio and peanut are used together, to reduce the cost in food production such as baklava, snack foods.DNA technology-based methods in food analysis are well-established and well-roundedtools for species differentiation, allergen detection. Especially, the probe-based TaqMan real-time PCR assay can amplify target DNA with efficiency, specificity, and sensitivity.In this study, pistachio, peanut and pea were finely ground and three separate series of triplet mixtures containing 0.1, 1, 10, 100, 1000, 10,000 and 100,000 mg kg-1 of each sample were prepared for each series, to a final weight of 100 g. DNA from reference samples and industrial products was successfully extracted with the GIDAGEN® Multi-Fast DNA Isolation Kit. TaqMan probes were designed for triplex determination of ITS, Ara h 3 and pea lectin genes which are specific regions for identification pistachio, peanut and pea, respectively.The real-time PCR as quantitative detected pistachio, peanut and pea in these mixtures down to the lowest investigated level of 0.1, 0.1 and 1 mg kg-1, respectively. Also, the methods reported here are capable of detecting of as little as 0.001% level of peanut DNA, 0,000001% level of pistachio DNA and 0.000001% level of pea DNA. We accomplish that the quantitative triplex real-time PCR method developed in this study canbe applied to detect pistachio, peanut and peatraces for three allergens at once in commercial food products.Keywords: allergens, DNA, real-time PCR, TaqMan probe
Procedia PDF Downloads 24616458 Anaerobic Digestion Batch Study of Taxonomic Variations in Microbial Communities during Adaptation of Consortium to Different Lignocellulosic Substrates Using Targeted Sequencing
Authors: Priyanka Dargode, Suhas Gore, Manju Sharma, Arvind Lali
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Anaerobic digestion has been widely used for production of methane from different biowastes. However, the complexity of microbial communities involved in the process is poorly understood. The performance of biogas production process concerning the process productivity is closely coupled to its microbial community structure and syntrophic interactions amongst the community members. The present study aims at understanding taxonomic variations occurring in any starter inoculum when acclimatised to different lignocellulosic biomass (LBM) feedstocks relating to time of digestion. The work underlines use of high throughput Next Generation Sequencing (NGS) for validating the changes in taxonomic patterns of microbial communities. Biomethane Potential (BMP) batches were set up with different pretreated and non-pretreated LBM residues using the same microbial consortium and samples were withdrawn for studying the changes in microbial community in terms of its structure and predominance with respect to changes in metabolic profile of the process. DNA of samples withdrawn at different time intervals with reference to performance changes of the digestion process, was extracted followed by its 16S rRNA amplicon sequencing analysis using Illumina Platform. Biomethane potential and substrate consumption was monitored using Gas Chromatography(GC) and reduction in COD (Chemical Oxygen Demand) respectively. Taxonomic analysis by QIIME server data revealed that microbial community structure changes with different substrates as well as at different time intervals. It was observed that biomethane potential of each substrate was relatively similar but, the time required for substrate utilization and its conversion to biomethane was different for different substrates. This could be attributed to the nature of substrate and consequently the discrepancy between the dominance of microbial communities with regards to different substrate and at different phases of anaerobic digestion process. Knowledge of microbial communities involved would allow a rational substrate specific consortium design which will help to reduce consortium adaptation period and enhance the substrate utilisation resulting in improved efficacy of biogas process.Keywords: amplicon sequencing, biomethane potential, community predominance, taxonomic analysis
Procedia PDF Downloads 51816457 Financial and Human Resources of Terrorism
Authors: Abdurrahman Karacabey
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Threat paradigm has shifted throughout the history. Considering conjuncture of our time, a major threat for humanity is terrorism. Although variety of reasons are influential, financial, and human resources are the vital needs for terrorist groups. It is known that terrorism is a significant term while taking decisions in diplomatic, politic, and military issues. Even though the methods to provide resources for terrorism are quite similar, there are still some differences for deterrent terrorist groups being active in various regions of the globe. Due to social and psychological reasons activists have generally similar excuses to join terrorist groups.At the same time, terrorists’ fiscal activities to secure permanence of terrorism, occupy the politics of the countries. Besides, preventive actions are expensive creating huge burdens in host nation’s economy. This paper elaborates on how ISIS is providing human and economic resources, course of actions to overcome ISIS is on the agenda of all countries.Keywords: financial resources, human resources, isis, terrorism
Procedia PDF Downloads 40016456 Separation and Purification of Oligostilbenes Using HPLC with Dereplication Strategy
Authors: Nurhuda Manshoor, Mohd Fazirulrahman Fathil, Muhammad Hakim Jaafar, Mohd Amirul S. A. Jalil
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The leaves of Neobalanocarpus heimii were investigated for their oligostilbene contents. Prior to isolation process, the determinations of compounds were based on mass spectrometric fragmentation patterns. Three compounds, heimiol B, hopeaphenol, and vaticaphenol A were identified directly from the crude extract. Preparative high-performance liquid chromatography (HPLC) was used to isolate and purify the other compounds. The purified compounds were then analyzed using NMR spectroscopy to identify the compound structure and stereochemistry. The method employed for the research modified to comply with different HPLC techniques such as preparative and analytical techniques. The crude sample was injected into preparative HPLC to obtain several fractions which consist of oligostilbene mixture. The fractions were further isolated using analytical HPLC to obtain four pure compounds. The compounds then were characterized using nuclear magnetic resonance (NMR). The result shows that the leaves extract of Neobalanocarpus heimii contain three oligostilbenes, namely vaticanol A, balanocarpol, and vaticaphenol A, and a galactopyranose.Keywords: balanocarpol, hemiol B, hopeaphenol, vaticanol A, vaticaphenol A
Procedia PDF Downloads 48316455 Deep Learning-Based Object Detection on Low Quality Images: A Case Study of Real-Time Traffic Monitoring
Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau
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The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems
Procedia PDF Downloads 18816454 Greening of Supply Chains: Benefits and Challenges Faced
Authors: Anurag Reddy Ramireddy, Abrar Ahmed, G. Sourya Sri Harsha, Pushkala Muralidharan
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Supply chains have been developing over time since the inception of commercial trade and barter. The Green Supply Chain Management (GSCM) is a powerful way to differentiate a company from its competitors and it can greatly influence the plan success. With increased awareness to corporate responsibility and the requirement to meet the terms with environmental policy, GSCM is becoming increasingly important for companies. This paper explains the concept of green supply chain management, the difference between conventional supply chain management and green supply management and how GSCM benefits organizations while at the same time supporting a sustainable environment system. An effort has also been made to analyse research already done in this field while exploring the challenges and barriers that organizations face in implementing GSCM practices in their existing systems.Keywords: corporate social responsibility, green supply chain management, sustainability
Procedia PDF Downloads 37116453 Leveraging Power BI for Advanced Geotechnical Data Analysis and Visualization in Mining Projects
Authors: Elaheh Talebi, Fariba Yavari, Lucy Philip, Lesley Town
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The mining industry generates vast amounts of data, necessitating robust data management systems and advanced analytics tools to achieve better decision-making processes in the development of mining production and maintaining safety. This paper highlights the advantages of Power BI, a powerful intelligence tool, over traditional Excel-based approaches for effectively managing and harnessing mining data. Power BI enables professionals to connect and integrate multiple data sources, ensuring real-time access to up-to-date information. Its interactive visualizations and dashboards offer an intuitive interface for exploring and analyzing geotechnical data. Advanced analytics is a collection of data analysis techniques to improve decision-making. Leveraging some of the most complex techniques in data science, advanced analytics is used to do everything from detecting data errors and ensuring data accuracy to directing the development of future project phases. However, while Power BI is a robust tool, specific visualizations required by geotechnical engineers may have limitations. This paper studies the capability to use Python or R programming within the Power BI dashboard to enable advanced analytics, additional functionalities, and customized visualizations. This dashboard provides comprehensive tools for analyzing and visualizing key geotechnical data metrics, including spatial representation on maps, field and lab test results, and subsurface rock and soil characteristics. Advanced visualizations like borehole logs and Stereonet were implemented using Python programming within the Power BI dashboard, enhancing the understanding and communication of geotechnical information. Moreover, the dashboard's flexibility allows for the incorporation of additional data and visualizations based on the project scope and available data, such as pit design, rock fall analyses, rock mass characterization, and drone data. This further enhances the dashboard's usefulness in future projects, including operation, development, closure, and rehabilitation phases. Additionally, this helps in minimizing the necessity of utilizing multiple software programs in projects. This geotechnical dashboard in Power BI serves as a user-friendly solution for analyzing, visualizing, and communicating both new and historical geotechnical data, aiding in informed decision-making and efficient project management throughout various project stages. Its ability to generate dynamic reports and share them with clients in a collaborative manner further enhances decision-making processes and facilitates effective communication within geotechnical projects in the mining industry.Keywords: geotechnical data analysis, power BI, visualization, decision-making, mining industry
Procedia PDF Downloads 8516452 Effectuation in Production: How Production Managers Can Apply Decision-Making Techniques of Successful Entrepreneurs
Authors: Malte Brettel, David Bendig, Michael Keller, Marius Rosenberg
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What are the core competences necessary in order to sustain manufacturing in high-wage countries? Aspiring countries all over the world gain market share in manufacturing and rapidly close the productivity and quality gap that has until now protected some parts of the industry in Europe and the United States from dislocation. However, causal production planning and manufacturing, the basis for productivity and quality, is challenged by the ever-greater need for flexibility and customized products in an uncertain business environment. This article uses a case-study-based approach to assess how production managers in high-wage countries can apply decision-making principals from successful entrepreneurs. 'Effectuation' instead of causal decision making can be applied to handle uncertainty of mass customization, to seek the right partners in alliances and to advance towards virtual production. The findings help managers to use their resources more efficiently and contribute to bridge the gap between production research and entrepreneurship.Keywords: case studies, decision-making behavior, effectuation, production planning
Procedia PDF Downloads 33916451 Range Suitability Model for Livestock Grazing in Taleghan Rangelands
Authors: Hossein Arzani, Masoud Jafari Shalamzari, Z. Arzani
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This paper follows FAO model of suitability analysis. Influential factors affecting extensive grazing were determined and converted into a model. Taleghan rangelands were examined for common types of grazing animals as an example. Advantages and limitations were elicited. All range ecosystems’ components affect range suitability but due to the time and money restrictions, the most important and feasible elements were investigated. From which three sub-models including water accessibility, forage production and erosion sensitivity were considered. Suitable areas in four levels of suitability were calculated using GIS. This suitability modeling approach was adopted due to its simplicity and the minimal time that is required for transforming and analyzing the data sets. Managers could be benefited from the model to devise the measures more wisely to cope with the limitations and enhance the rangelands health and condition.Keywords: range suitability, land-use, extensive grazing, modeling, land evaluation
Procedia PDF Downloads 33316450 Optimization of Photocatalytic Degradation of Para-Nitrophenol in Visible Light by Nitrogen and Phosphorus Co-Doped Zinc Oxide Using Factorial Design of Experimental
Authors: Friday Godwin Okibe, Elaoyi David Paul, Oladayo Thomas Ojekunle
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In this study, Nitrogen and Phosphorous co-doped Zinc Oxide (NPZ) was prepared through a solvent-free reaction. The NPZ was characterized by Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) spectroscopy. The photocatalytic activity of the catalyst was investigated by monitoring the degradation of para-nitrophenol (PNP) under visible light irradiation and the process was optimized using factorial design of experiment. The factors investigated were initial concentration of para-nitrophenol, catalyst loading, pH and irradiation time. The characterization results revealed a successful doping of ZnO by nitrogen and phosphorus and an improvement in the surface morphology of the catalyst. The photo-catalyst exhibited improved photocatalytic activity under visible light by 73.8%. The statistical analysis of the optimization result showed that the model terms were significant at 95% confidence level. Interactions plots revealed that irradiation time was the most significant factor affecting the degradation process. The cube plots of the interactions of the variables showed that an optimum degradation efficiency of 66.9% was achieved at 10mg/L initial PNP concentration, 0.5g catalyst loading, pH 7 and 150 minutes irradiation time.Keywords: nitrogen and phosphorous co-doped Zno, p-nitrophenol, photocatalytic degradation, optimization, factorial design of experimental
Procedia PDF Downloads 51616449 Numerical Analysis of the Aging Effects of RC Shear Walls Repaired by CFRP Sheets: Application of CEB-FIP MC 90 Model
Authors: Yeghnem Redha, Guerroudj Hicham Zakaria, Hanifi Hachemi Amar Lemiya, Meftah Sid Ahmed, Tounsi Abdelouahed, Adda Bedia El Abbas
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Creep deformation of concrete is often responsible for excessive deflection at service loads which can compromise the performance of elements within a structure. Although laboratory test may be undertaken to determine the deformation properties of concrete, these are time-consuming, often expensive and generally not a practical option. Therefore, relatively simple empirically design code models are relied to predict the creep strain. This paper reviews the accuracy of creep and shrinkage predictions of reinforced concrete (RC) shear walls structures strengthened with carbon fibre reinforced polymer (CFRP) sheets, which is characterized by a widthwise varying fibre volume fraction. This review is yielded by CEB-FIB MC90 model. The time-dependent behavior was investigated to analyze their static behavior. In the numerical formulation, the adherents and the adhesives are all modelled as shear wall elements, using the mixed finite element method. Several tests were used to dem¬onstrate the accuracy and effectiveness of the proposed method. Numerical results from the present analysis are presented to illustrate the significance of the time-dependency of the lateral displacements.Keywords: RC shear walls strengthened, CFRP sheets, creep and shrinkage, CEB-FIP MC90 model, finite element method, static behavior
Procedia PDF Downloads 30116448 Health and Safety Risk Assesment with Electromagnetic Field Exposure for Call Center Workers
Authors: Dilsad Akal
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Aim: Companies communicate with each other and with their costumers via call centers. Call centers are defined as stressful because of their uncertain working hours, inadequate relief time, performance based system and heavy workload. In literature, this sector is defined as risky as mining sector by means of health and safety. The aim of this research is to enlight the relatively dark area. Subject and Methods: The collection of data for this study completed during April-May 2015 for the two selected call centers in different parts of Turkey. The applied question mostly investigated the health conditions of call center workers. Electromagnetic field measurements were completed at the same time with applying the question poll. The ratio of employee accessibility noted as 73% for the first call center and 87% for the second. Results: The results of electromagnetic field measurements were as between 371 V/m-32 V/m for the first location and between 370 V/m-61 V/m for the second. The general complaints of the employees for both workplaces can be counted as; inadequate relief time, inadequate air conditioning, disturbance, poor thermal conditions, inadequate or extreme lighting. Furthermore, musculoskeletal discomfort, stress, ear and eye discomfort are main health problems of employees. Conclusion: The measured values and the responses to the question poll were found parallel with the other similar research results in literature. At the end of this survey, a risk map of workplace was prepared in terms of safety and health at work in general and some suggestions for resolution were provided.Keywords: call center, health and safety, electromagnetic field, risk map
Procedia PDF Downloads 17716447 A Randomized Comparative Evaluation of Efficacy of Ultrasound Guided Costoclavicular and Supraclavicular Approaches of Brachial Plexus Block for Upper Limb Surgeries
Authors: Anshul, Rajni Kalia, Sachin Kumar
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Introduction: The costoclavicular approach, a modification to the infraclavicular approach, has been described for anesthesia for upper limb surgeries. Material And Methods: In this randomized and single-blind study, fourty patients undergoing emergency/elective upper limb surgery were allocated to two groups. Group C and S received ultrasound-guided Costoclavicular block and Supraclavicular block, respectively, with 20 ml 0.5 % ropivacaine with 8 mg dexamethasone under strict asepsis. The primary outcome assessed was the total duration of sensory and motor block in the postoperative period. Secondary outcomes were to compare the time taken to perform the procedure, block characteristics in terms of onset of motor and sensory blockade, the efficacy of analgesia with respect to the time of administration of the first rescue analgesic dose with both the blocks and note the side effects pertaining to either of the blocks. Results: The mean total duration of sensory and motor blockade was longer in group C vs. group S (p=0.002 and 0.024, respectively). The mean duration to perform a block in group S was more than in group C (p=0.012). The mean onset of sensory and motor Blockade Time in group S was more than in group C (p<0.001 and <0.001, respectively). The mean duration to perform a block in group S was more than in group C (p=0.012). Conclusion: The costoclavicular approach is better than supraclavicular in terms of rapid execution, faster onset of sensory-motor blockade, prolonged postoperative analgesia and similar PONV and safety profile.Keywords: costoclavicular, supraclavicular, ropivacaine, dexamethasone
Procedia PDF Downloads 6116446 Performance Comparison of Joint Diagonalization Structure (JDS) Method and Wideband MUSIC Method
Authors: Sandeep Santosh, O. P. Sahu
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We simulate an efficient multiple wideband and nonstationary source localization algorithm by exploiting both the non-stationarity of the signals and the array geometric information.This algorithm is based on joint diagonalization structure (JDS) of a set of short time power spectrum matrices at different time instants of each frequency bin. JDS can be used for quick and accurate multiple non-stationary source localization. The JDS algorithm is a one stage process i.e it directly searches the Direction of arrivals (DOAs) over the continuous location parameter space. The JDS method requires that the number of sensors is not less than the number of sources. By observing the simulation results, one can conclude that the JDS method can localize two sources when their difference is not less than 7 degree but the Wideband MUSIC is able to localize two sources for difference of 18 degree.Keywords: joint diagonalization structure (JDS), wideband direction of arrival (DOA), wideband MUSIC
Procedia PDF Downloads 461