Search results for: food patterns

Authors: S. Tartaya, R. Bagtache, A. M. Djaballah, M. Trari

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Due to the increase in the trade of colored products and their applications in various fields such as cosmetic, food, textile, pharmaceutical industries, etc. Dyes constitute a large part of the contaminants in wastewater and cause serious damage in the environment and the aquatic system. Photocatalytic systems are highly efficient processes for treating wastewater in the presence of semiconductor photocatalysts. In this field, we report our contribution by synthesizing a potassium vanadium fluorophosphate compound KVPO4F (which is abbreviated KVPOF) by a simplified hydrothermal method at 180°C for 5 days. The as synthesized product has been characterized physically and photoelectrochemically. The indirect optical transition of 1.88 eV, determined from the diffuse reflectance, was assigned to the charge transfer. Moreover, the curve (C-2–E) of the KVPOF displayed n-type character of the semiconductor. Even more, interestingly, the photocatalytic performance was evaluated through the photo-degradation of cationic dye Methyl Violet (MV). An abatement of 61% was obtained after 6 h of irradiation under visible light.

Keywords: KVPO4F, photocatalysis, semiconductor, wastewater, environment

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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Authors: D. S. Gurjar, R. Kaur, K. P. Singh, R. Singh

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A greater volume of wastewater generate from urban areas in India. Due to the adequate availability, less energy requirement and nutrient richness, farmers of urban and peri-urban areas are deliberately using wastewater to grow high value vegetable crops. Wastewater contains pathogens and toxic pollutants, which can enter in the food chain system while using wastewater for irrigating vegetable crops. Hence, wastewater can use for growing commercial flower crops that may avoid food chain contamination. Tuberose (Polianthes tuberosa L.) is one of the most important commercially grown, cultivated over 30, 000 ha area, flower crop in India. Its popularity is mainly due to the sweet fragrance as well as the long keeping quality of the flower spikes. The flower spikes of tuberose has high market price and usually blooms during summer and rainy seasons when there is meager supply of other flowers in the market. It has high irrigation water requirement and fresh water supply is inadequate in tuberose growing areas of India. Therefore, wastewater may fulfill the water and nutrients requirements and may enhance the productivity of tuberose. Keeping in view, the present study was carried out at WTC farm of ICAR-Indian Agricultural Research Institute, New Delhi in 2014-15. Prajwal was the variety of test crop. The seven treatments were taken as T-1. Wastewater irrigation at 0.6 ID/CPE, T-2: Wastewater irrigation at 0.8 ID/CPE, T-3: Wastewater irrigation at 1.0 ID/CPE, T-4: Wastewater irrigation at 1.2 ID/CPE, T-5: Wastewater irrigation at 1.4 ID/CPE, T-6: Conjunctive use of Groundwater and Wastewater irrigation at 1.0 ID/CPE in cyclic mode, T-7: Control (Groundwater irrigation at 1.0 ID/CPE) in randomized block design with three replication. Wastewater and groundwater samples were collected on monthly basis (April 2014 to March 2015) and analyzed for different parameters of irrigation quality (pH, EC, SAR, RSC), pollution hazard (BOD, toxic heavy metals and Faecal coliforms) and nutrients potential (N, P, K, Cu, Fe, Mn, Zn) as per standard methods. After harvest of tuberose crop, soil samples were also collected and analyzed for different parameters of soil quality as per standard methods. The vegetative growth and flower parameters were recorded at flowering stage of tuberose plants. Results indicated that wastewater samples had higher nutrient potential, pollution hazard as compared to groundwater used in experimental crop. Soil quality parameters such as pH EC, available phosphorous & potassium and heavy metals (Cu, Fe, Mn, Zn, Cd. Pb, Ni, Cr, Co, As) were not significantly changed whereas organic carbon and available nitrogen were significant higher in the treatments where wastewater irrigations were given at 1.2 and 1.4 ID/CPE as compared to groundwater irrigations. Significantly higher plant height (68.47 cm), leaves per plant (78.35), spike length (99.93 cm), rachis length (37.40 cm), numbers of florets per spike (56.53), cut spike yield (0.93 lakh/ha) and loose flower yield (8.5 t/ha) were observed in the treatment of Wastewater irrigation at 1.2 ID/CPE. Study concluded that given quality of wastewater improves the productivity of tuberose without an adverse impact on soil quality/health. However, its long term impacts need to be further evaluated.

Keywords: conjunctive use, irrigation, tuberose, wastewater

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Authors: Shih-Fang Lo, Tzu-Wei Guo, Chih-Hsuan Lee

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Tropical fisheries are vulnerable to the physical and biogeochemical oceanic changes associated with climate change. Warmer temperatures and extreme weather have beendamaging the abundance and growth patterns of aquatic organisms. In recent year, the shrinking of fish stock and labor shortage have increased the threat to global aquacultural production. Thus, building a climate-resilient and sustainable mechanism becomes an urgent, important task for global citizens. To tackle the problem, Taiwanese fishermen applies the artificial intelligence (AI) technology. In brief, the AI system (1) measures real-time water quality and chemical parameters infish ponds; (2) monitors fish stock through segmentation, detection, and classification; and (3) implements fishermen’sprevious experiences, perceptions, and real-life practices. Applying this system can stabilize the aquacultural production and potentially increase the labor force. Furthermore, this AI technology can build up a more resilient and sustainable system for the fishermen so that they can mitigate the influence of extreme weather while maintaining or even increasing their aquacultural production. In the future, when the AI system collected and analyzed more and more data, it can be applied to different regions of the world or even adapt to the future technological or societal changes, continuously providing the most relevant and useful information for fishermen in the world.

Keywords: aquaculture, artificial intelligence (AI), real-time system, sustainable fishery

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Authors: Yasin Bilim, Alaaddin Başoda

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The recent growth of internet applications on hospitality and tourism provokes on-line consumer comments and reviews. Many researchers and practitioners have named this enormous potential as “e-WOM (electronic word of mouth)”. Travel comments are important experiential information for the potential travellers. Many researches have been conducted to analyse the effects of e-WOM on hotel consumers. Broadly quantitative methods have been used for analysing online comments. But, a few studies have mentioned about the positive practical aspects of the comments for hotel marketers. The study aims to show different usage and effects of hotel consumers’ comments. As qualitative analysis method, grounded theory, content and discourse analysis, were used. The data based on the 10 resort hotel consumers’ on-line comments. Results show that consumers tend to write comments about service person, rooms, food services and pool in their online space. These indicators can be used by hotel marketers as a marketing information tool.

Keywords: comments, E-WOM, hotel consumer, qualitative

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Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

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Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

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Authors: Almas Rajguru, Archana Kamath, Rachana Singh

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The study aims to determine the depositional facies, high-resolution sequence stratigraphy, and diagenetic processes of Early Oligocene carbonates in N & N-W of Heera, Mumbai Offshore. Foraminiferal assemblage and microfacies from cores of Well A, B, C, D and E are indicative of facies association related to four depositional environments, i.e., restricted inner lagoons-tidal flats, shallow open lagoons, high energy carbonate bars-shoal complex and deeper mid-ramps of a westerly dipping homoclinal carbonate ramp. Two high-frequency (4th Order) depositional sequences bounded by sequence boundary, DS1 and DS2, displaying hierarchical stacking patterns, are identified and correlated across wells. Vadose zone diagenesis effect during short diastem/ subaerial exposure has rendered good porosity due to dissolution in HST carbonates and occasionally affected underlying TST sediments (Well D, C and E). On mapping and correlating the sequences, the presence of thin carbonate bars that can be potential reservoirs are envisaged along NW-SE direction, towards north and south of Wells E, D and C. A more pronounced development of these bars in the same orientation can be anticipated towards the west of the study area.

Keywords: sequence stratigraphy, depositional facies, diagenesis petrography, early Oligocene, Mumbai offshore

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Authors: Rakesh Namdeti

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The liquid waste-wastewater- is essentially the water supply of the community after it has been used in a variety of applications. In recent years, heavy metal concentrations, besides other pollutants, have increased to reach dangerous levels for the living environment in many regions. Among the heavy metals, Lead has the most damaging effects on human health. It can enter the human body through the uptake of food (65%), water (20%), and air (15%). In this background, certain low-cost and easily available biosorbent was used and reported in this study. The scope of the present study is to remove Lead from its aqueous solution using Olea EuropaeaResin as biosorbent. The results showed that the biosorption capacity of Olea EuropaeaResin biosorbent was more for Lead removal. The Langmuir, Freundlich, Tempkin, and Dubinin-Radushkevich (D-R) models were used to describe the biosorption equilibrium of Lead Olea EuropaeaResin biosorbent, and the biosorption followed the Langmuir isotherm. The kinetic models showed that the pseudo-second-order rate expression was found to represent well the biosorption data for the biosorbent.

Keywords: novel biosorbent, central composite design, Lead, isotherms, kinetics

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Authors: Oshin Anand, Atanu Rakshit

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The vast increment in the e-commerce ventures makes this area a prominent research stream. Besides several quantified parameters, the textual content of reviews is a storehouse of many information that can educate companies and help them earn profit. This study is an attempt in this direction. The article attempts to categorize data based on a computed metric that quantifies the influencing capacity of reviews rendering two categories of high and low influential reviews. Further, each of these document is studied to conclude several product feature categories. Each of these categories along with the computed metric is converted to linguistic identifiers and are used in an association mining model. The article makes a novel attempt to combine feature attraction with quantified metric to categorize review text and finally provide frequent patterns that depict customer preferences. Frequent mentions in a highly influential score depict customer likes or preferred features in the product whereas prominent pattern in low influencing reviews highlights what is not important for customers. This is achieved using a hybrid approach of text mining for feature and term extraction, sentiment analysis, multicriteria decision-making technique and association mining model.

Keywords: association mining, customer preference, frequent pattern, online reviews, text mining

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Authors: R. S. Yadav, J. Havlica, I. Kuřitka, Z. Kozakova, J. Masilko, L. Kalina, M. Hajdúchová, V. Enev, J. Wasserbauer

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Nickel spinel ferrite NiFe2O4 nanoparticles with different particle size at different annealing temperature were synthesized using the starch-assisted sol-gel auto-combustion method. The synthesized nanoparticles were characterized by conventional powder X-ray diffraction (XRD) spectroscopy, Raman Spectroscopy, Fourier Transform Infrared Spectroscopy, Field-Emission Scanning Electron Microscopy, X-ray Photoelectron Spectroscopy and Vibrating Sample Magnetometer. The XRD patterns confirmed the formation of NiFe2O4 spinel ferrite nanoparticles. Field-Emission Scanning Electron Microscopy revealed that particles are of spherical morphology with particle size 5-20 nm at lower annealing temperature. An infrared spectroscopy study showed the presence of two principal absorption bands in the frequency range around 525 cm-1 (ν1) and around 340 cm-1 (ν2); which indicate the presence of tetrahedral and octahedral group complexes, respectively, within the spinel ferrite nanoparticles. Raman spectroscopy study also indicated the change in octahedral and tetrahedral site related Raman modes in nickel ferrite nanoparticles with change of particle size. This change in magnetic behavior with change of particle size of NiFe2O4 nanoparticles was observed.

Keywords: nickel ferrite, nanoparticles, magnetic property, NiFe2O4

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Authors: Sahira N. Muslim, Alaa N. Mohammed, Saba Saadoon Khazaal, Batool Kadham Salman, Israa M. S. AL-Kadmy, Sraa N. Muslim, Ahmed S. Dwaish, Sawsan Mohammed Kareem, Sarah N. Aziz, Ruaa A. Jasim

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Tannase has wide applications in food, beverage, brewing, cosmetics and chemical industries and one of the major applications of tannase is the production of gallic acid. Gallic acid is used for manufacturing of trimethoprim. In the present study, a local fungal strain of Penicillium expansum A₄ isolated from spoilt apple samples gave the highest production level of tannase. Tannase was partially purified with a recovery yield of 92.52% and 6.32 fold of purification by precipitation using ammonium sulfate at 50% saturation. Tannase led to increased antimicrobial activity of ceftazidime against Pseudomonas aeruginosa and S. aureus and had a synergism effect at low concentrations of ceftazidime, and thus, tannase may be a useful adjuvant agent for the treatment of many bacterial infections in combination with ceftazidime.

Keywords: ceftazidime, Penicillium expansum, tannase, antimicrobial activity

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Authors: Ghazi Faisal Najmuldeen, Noridah Abdullah, Mimi Sakinah

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Bioethanol is an alcohol made by fermentation, mostly from carbohydrates, Cellulosic biomass, derived from non-food sources, such as castor shell waste, is also being developed as a feedstock for ethanol production Cellulose extracted from biomass sources is considered the future feedstock for many products due to the availability and eco-friendly nature of cellulose. In this study, castor shell (CS) biowaste resulted from the extraction of Castor oil from castor seeds was evaluated as a potential source of cellulose. The cellulose was extracted after pretreatment process was done on the CS. The pretreatment process began with the removal of other extractives from CS, then an alkaline treatment, bleaching process with hydrogen peroxide, and followed by a mixture of acetic and nitric acids. CS cellulose was analysed by infrared absorption spectroscopy (FTIR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and thermogravimetric analysis (TGA). The result showed that the overall process was adequate to produce cellulose with high purity and crystallinity from CS waste. The cellulose was then hydrolyzed to produce glucose and then fermented to bioethanol.

Keywords: bioethanol, castor shell, cellulose, biowaste

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Authors: Mohamed Abdullah Ahmed

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In a study of chickpea protein isolate (CPI) preparation, the wet alkaline extraction was carried out. The objectives were to determine the optimal extracting conditions of CPI and apply CPI into a sponge cake recipe to replace egg and make acceptable product. The design used in extraction was a central composite design. The response surface methodology was preferred to graphically express the relationship between extraction time and pH with the output variables of percent yield and protein content of CPI. It was noted that optimal extracting conditions were 60 min and pH 10.5 resulting in 90.07% protein content and 89.15% yield of CPI. The protein isolate (CPI) could be incorporated in cake to 20% without adversely affecting the cake physical properties such as cake hardness and sensory attributes. The higher protein content in cake was corresponding to the amount of CPI added. Therefore, adding CPI can significantly (p<0.05) increase protein content in cake. However, sensory evaluation showed that adding more than 20% of CPI decreased the overall acceptability. The results of this investigation could be used as a basic knowledge of CPI utilization in other food products.

Keywords: chick bean protein isolate, sponge cake, utilization, sponge

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Authors: Gaurav Kumar Sinha

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The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

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Authors: Pawamana Ramachandra, Jitesh Gupta, Saranga P. Pogula

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In verification of high volume and complex packet processing IPs, finer control of flow management aspects (for example, rate, bits/sec etc.) per flow class (or a virtual channel or a software thread) is needed. When any Software/Universal Verification Methodology (UVM) thread arbitration is left to the simulator (e.g., Verilog Compiler Simulator (VCS) or Incisive Enterprise Simulator core simulation engine (NCSIM)), it is hard to predict its pattern of resulting distribution of bandwidth by the simulator thread arbitration. In many cases, the patterns desired in a test scenario may not be accomplished as the simulator might give a different distribution than what was required. This can lead to missing multiple traffic scenarios, specifically deadlock and starvation related. We invented a component (namely Flow Manager Verification IP) to be intervening between the application (test case) and the protocol VIP (with UVM sequencer) to control the bandwidth per thread/virtual channel/flow. The Flow Manager has knobs visible to the UVM sequence/test to configure the required distribution of rate per thread/virtual channel/flow. This works seamlessly and produces rate stimuli to further harness the Design Under Test (DUT) with asymmetric inputs compared to the programmed bandwidth/Quality of Service (QoS) distributions in the Design Under Test.

Keywords: flow manager, UVM sequencer, rated traffic generation, quality of service

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Authors: X. Gu, K. L. Blackmore

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The impact factor was introduced to measure the quality of journals. Various impact measures exist from multiple bibliographic databases. In this research, we aim to provide a broader understanding of the relationship between scholarly impact and other characteristics of academic journals. Data used for this research were collected from Ulrich’s Periodicals Directory (Ulrichs), Cabell’s (Cabells), and SCImago Journal & Country Rank (SJR) from 1999 to 2015. A master journal dataset was consolidated via Journal Title and ISSN. We adopted a two-step analysis process to study the quantitative relationships between scholarly impact and other journal characteristics. Firstly, we conducted a correlation analysis over the data attributes, with results indicating that there are no correlations between any of the identified journal characteristics. Secondly, we examined the quantitative relationship between scholarly impact and other characteristics using quartile analysis. The results show interesting patterns, including some expected and others less anticipated. Results show that higher quartile journals publish more in both frequency and quantity, and charge more for subscription cost. Top quartile journals also have the lowest acceptance rates. Non-English journals are more likely to be categorized in lower quartiles, which are more likely to stop publishing than higher quartiles. Future work is suggested, which includes analysis of the relationship between scholars and their publications, based on the quartile ranking of journals in which they publish.

Keywords: academic journal, acceptance rate, impact factor, journal characteristics

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Authors: Tesfaye Fentaw Nigatu, Alexander Trupp, Teh Pek Yen

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Research on museums and the experiences of visitors has flourished in recent years, especially after museums became centers of edutainment beyond preserving heritage resources. This paper aims to comprehensively understand the changes, continuities, and future research development directions of museum visitors’ experiences. To identify current research trends, the paper summarizes and analyses research article publications from 1986 to 2023 on museum visitors' experiences. Bibliometric analysis software VOSviewer and Harzing POP (Publish or Perish) were used to analyze 407 academic articles. The articles were generated from the Scopus database. The study attempted to map new insights for future scholars and academics to expand the scope of museum visitors’ experience studies by analyzing keywords, citation patterns, influential articles in the field, publication trends, collaborations between authors, institutions, and clusters of highly cited articles. Accessibility to museums, social media usage within museums, aesthetics in museum settings, mixed reality experiences, sustainability issues, and emotions have emerged as key research areas in the study of museum visitors' experiences. The results benefit stakeholders and researchers in advancing the collective progress of considering recent research trends to stay informed about the latest developments and breakthroughs in the global academic landscape and visitors’ experiences development in the museum.

Keywords: bibliometric analysis, museum, network analysis, visitors’ experiences, visual analysis

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Authors: R. Govender, T. C. Katsande, E. Madoroba, N. M. Thiebaut, D. Naidoo

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South African control over meat safety is managed by the Department of Agriculture, Forestry and Fisheries (DAFF). Veterinary services department in each of the nine provinces in the country is tasked with overseeing the farm and abattoir segments of the meat supply chain. Abattoirs are privately owned. The number of abattoirs over the years has increased. This increase has placed constraints on government resources required to monitor these abattoirs. This paper presents empirical research results on the hygienic processing of meat in high and low throughout abattoirs. This paper presents a case for the adoption of risk-based regulation as a method of government control over hygiene and safe meat processing at abattoirs in South Africa. Recommendations are made to the DAFF regarding policy considerations on risk-based regulation as a model of control in South Africa.

Keywords: risk-based regulation, abattoir, food control, meat safety

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Authors: I. Tulay Cagatay

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Blue-green microalgae cyanobacteria, which are important photosynthetic organisms of aquatic ecosystems, are the primary sources of many bioactive compounds such as proteins, carbohydrates, lipids, vitamins and enzymes that can be used as antimicrobial and antiviral agents. Some of these organisms are nowadays used directly in the food, cosmetic and pharmaceutical industry, or in aquaculture and biotechnological approaches like biofuel or drug therapy. Finding the effective, environmental friendly chemotropic and antimicrobial agents to control fish pathogens are crucial in a country like Turkey which has a production capacity of about 240 thousand tons of cultured fish and has 2377 production farms and which is the second biggest producer in Europe. In our study, we tested the antimicrobial activity of cyanobacterium spp. against some fish pathogens Aeromonas hydrophila and Yersinia ruckeri that are important pathogens for rainbow trout farms. Agar disk diffusion test method was used for studying antimicrobial activity on pathogens. Both tested microorganisms have shown antimicrobial activity positively as the inhibition zones were 0.45 mm and 0.40 mm respectively.

Keywords: fish pathogen, cyanobacteria, antimicrobial activity, trout

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Authors: Kayijuka Idrissa

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This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.

Keywords: statistical methods, traffic flow, Poisson distribution, car moving technics

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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Authors: Azita Behbahaninia

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Soil and surface and ground waters pollution to arsenic (As) due to its high potential for food cycle entrance, has high risk for human safety. Also, this pollution can cause quality and quantity decreasing of agricultural products or some lesions in farm animals that due to low knowledge, its reason is unknown, but can relate to As pollution. This study was conducted to investigate level of soil and water pollution by As in Hashtrood city. Based on the region’s information, the surface and ground waters, soil, river sediments, and rock were sampled and analyzed for physico-chemical and As in lab. There are significant differences for mean contents between As in the samples and crust. The maximum levels of As were observed in fly ash sample. Consequently, As pollution was related to geogenic and volcanic eruptions in this region. These mechanisms are diagnosed as As pollution in the region: As release for the rock units, As sorption by oxide minerals in aerobic and acidic to neutral conditions, desorption from oxide surfaces with pH increasing, increasing of As concentration in solution, and consequently pollution.

Keywords: arsenic, flyash, groundwater, soil

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Authors: Renate Gericke, Carol Long

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Despite the robust empirical support of attachment, advancement in the description and conceptualization of attachment has been slow and has not significantly advanced beyond the identification of attachment security or type (namely, secure, avoidant, ambivalent and disorganized). This has continued despite papers arguing for theoretical refinement in the classification of attachment presentations. For thinking and practice to advance, it is critically important that these categories and their assessment be interrogated in different contexts and across developmental age. To achieve this, a quantitative design was used with descriptive and inferential statistics, and general linear models were employed to analyze the data. The Attachment Story Completion Test (ASCT) was administered to 105 children between the ages of eight and twelve from socio-economically deprived contexts with high exposure to trauma. A staggering 93% of the children had insecure attachments (specifically, avoidant 37%, disorganized 34% and ambivalent 22%) and attachment was more complex than currently conceptualized in the attachment literature. Primary attachment did not only present as one of four discreet categories, but 70% of the sample had a complex attachment with more than one type of maternal attachment style. Attachment intensity also varied along a continuum (between 1 and 5). The findings have implications for a) research that has not considered the potential complexity of attachment or attachment intensity, b) policy to more actively support mother-infant dyads, particularly in high-risk contexts and c) question the applicability of a western conceptualization of a primary maternal attachment figure in non-western collectivist societies.

Keywords: attachment, children at risk, middle childhood, non-western context

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Authors: Sahil Kapahi

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A Formula SAE competition is characterized by typical track layouts having slaloms, tight corners and short straights, which favor a particular range of engine speed for a given set of gear ratios. Therefore, it is imperative that the power-train is optimized for the corresponding engine rpm band. This paper describes the process of designing, simulating and validating an air intake manifold for an inline four cylinder four-stroke internal combustion gasoline engine based on analysis of required vehicle performance. The requirements for the design of subject intake were set considering the rules of FSAE competitions and analysis of engine performance patterns for typical competition scenarios, carried out using OPTIMUMLAP software. Manifold geometry was optimized using results of air flow simulations performed on ANSYS CFX, and subsequent effect of this geometry on the engine was modeled using 1D simulation on Ricardo WAVE. A design was developed to meet the targeted performance standards in terms of engine torque output and volumetric efficiency. Finally, the intake manifold was manufactured and assembled onto the vehicle, and the engine output of the vehicle with the designed intake was studied using a dynamometer. The results of the dynamometer testing were then validated against predicted values derived from the Ricardo WAVE modeling and benefits to performance of the vehicle were established.

Keywords: 1 D Simulation, air flow simulation, ANSYS CFX, four-stroke engine, OPTIMUM LAP, Ricardo WAVE

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Authors: Emine G. Cansu Ergun

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Conjugated system based sensors for selective detection of metal ions have been taking attention during last two decades. Fluorescent sensors are the promising candidates for ion detection due to their high selectivity towards metal ions, and rapid response times. Detection of mercury in an environmenet is important since mercury is a toxic element for human. Beyond the maximum allowable limit, mercury may cause serious problems in human health by spreading into the atmosphere, water and the food chain. In this study, a quinoxaline and 3,4-ethylenedioxy thiophene based donor-acceptor-donor type conjugated molecule used as a fluorescent sensor for detecting the mercury ion in aqueous medium. Among other various cations, existence of mercury resulted in a full quenching of the fluorescence signal. Then, a paper based sensor is constructed and used for mercury detection. As a result it is concluded that the offering sensor is a good candidate for selective mercury detection in aqueous media both in solution and paper based forms.

Keywords: Conjugated molecules , fluorescence quenching, metal ion detection , sensors

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Authors: Sumonthip Kongtun Janphuk

Abstract:

Ten cereal grains that usually used as ingredients in healthy products were studied for phytosteryl glucoside contents. β-sitosteryl glucoside in 10 cereal grains, including Phasecolus vulgaris L. (kidney bean), Sorghum bicolor (sorghum), Moringa oleifera Lam. (drumstick), Nelumbo nucifera (lotus), Vigna radiate L. (mung bean), Coix lacrymajobi (job’tears), Oryza sativa. (red rice), Glycine max L. Merrill. (soybean),Cucurbita maschata Decne (pumpkin) and Helianthas annuus (sunflower seeds), were analyzed using Thin-layer chromatography (TLC) and High-Performance liquid chromatography (HPLC). All grains were extracted with methanol before analysis. Red bean showed the maximum phytosteryl glucoside content of 0.42% w/w. The content of others were as follows: pumpkin seed 0.173%, mung bean 0.099 %, soybean 0.07%, dried moringa seed 0.067%, lotus seed 0.044%, sorghum 0.032%, sunflower seed 0.016%, Job's tears 0.012%, and brown rice 0.006%.

Keywords: cereal grains, phytosterol, β-sitosteryl glucoside, food analysis.

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Authors: Neda Gegar Goshe, Hossein Rassi

Abstract:

The antibacterial properties of macrolide antibiotics (such as erythromycin and tylosin) depend ultimately on the glycosylation of otherwise inactive polyketide lactones. Among the sugars commonly found in such macrolides are various 6-deoxyhexoses including the 3-dimethylamino sugars mycaminose and desosamine (4-deoxymycaminose). Some macrolides (such as tylosin) possess multiple sugar moieties, whereas others (such as erythromycin) have two sugar substituents. Streptomyces fradiae is an ideal host for development of generic polyketide-overproducing strains because it contains three of the most common precursors-malonyl-CoA, methylmalonyl-CoA and ethylmalonyl-CoA-used by modular PKS, and is a host that is amenable to genetic manipulation. As patterns of glycosylation markedly influence a macrolide's drug activity, there is considerable interest in the possibility of using combinatorial biosynthesis to generate new pairings of polyketide lactones with sugars, especially 6-deoxyhexoses. Here, we report a successful attempt to alter the aminodeoxyhexose-biosynthetic capacity of Streptomyces fradiae (a producer of tylosin) by importing genes from the erythromycin producer Saccharopolyspora erythraea. The biotransformation of erythromycin-D into the desired major component erythromycin-A involves two final enzymatic reactions, EryK-catalyzed hydroxylation at the C-12 position of the aglycone and EryG-catalyzed O methylation at the C-3 position of macrose .This engineered S. fradiae produced substantial amounts of two potentially useful macrolides that had not previously been obtained by fermentation.

Keywords: Streptomyces fradiae, eryK and eryG genes, tylosin, antibiotics

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Authors: Sadeeqa Khan, Muhammad Usman

Abstract:

Employees’ knowledge hiding behaviors can be detrimental to employees’ interpersonal relationships and individual and organizational learning and creativity. However, to the best of the authors’ knowledge, the literature on the contingencies, antecedents and outcomes of employees’ knowledge hiding behaviors is still in its infancy. On the other hand, not everyone who hides knowledge hides it the same way, as individuals are different, so do their behaviors. This study explores the links between employees’ personality traits and their knowledge hiding behaviors. By using a single case study as a research methodology and collecting data through 28 semi-structured interviews from employees working in Alpha Electronics (the pseudo name of the company to ascertain anonymity) operating in Pakistan, we foreground the patterns of relationships between employees’ personality traits and knowledge hiding behaviors – rationalized hiding, evasive hiding and playing dumb. Our findings suggest that employees high on extraversion involve in evasive knowledge hiding; while employees low on extraversion (introverts) demonstrate rationalized hiding. Moreover, both extrovert and introvert employees involve in playing dumb in situations that involve risk for their jobs and careers. For instance, when knowledge is requested from their managers, both extrovert and introvert employees tend to play dumb, as in such cases, evasive and rationalized hiding can be harmful to their job and career-related interests and motives. Other than theoretical contributions, the study offers important implications for organizations faced with the challenges of shortage of skills and knowledge.

Keywords: knowledge hiding, personality, rationalized hiding, playing dumb, evasive hiding

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Authors: Hassan Adedoyin Rasaq

Abstract:

The marketing efforts of the present day business is not just geared towards meeting the consumer’s needs at a price, but ensuring good customer satisfaction, and strategizing on how to retain such customers. Customer satisfaction and retention is achievable through the co-ordination of the marketing mixes; Product, Price, Promotion and Place; Relationship Marketing; After-Sales Service; Rebates/Discounts/Price reduction policy and Total Quality Management (TQM). A first-hand customer, If well satisfied, will become a company’s repeat customer, proceeds to become a client and goes further to become an advocate of the company by applauding the company’s products/services and encouraging others to buy from it. It is the objective of this paper, therefore, to guide business organizations on how to enhance customer satisfaction, and retain existing customers as a means of long-term survival in marketing. The responses of 72 randomly selected Marketing personnel spread across three (3) food and beverage companies in Nigeria were analyzed. One hypothesis was tested using a one-way analysis of variance (ANOVA) statistical tool, and it was discovered that Relationship marketing contributed to organizational profitability and growth.

Keywords: customer satisfaction, retention strategies, marketing, marketing mixes

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Authors: Naima Nur, Safa Islam, Saeema Islam, Faridul Alam

Abstract:

Background: Drug-resistant pulmonary tuberculosis (DR-PTB), particularly multidrug-resistant tuberculosis (MDR-TB) and pre-extensive drug-resistant (pre-XDR), is a major challenge in effectively controlling TB, especially in developing. This study aimed to identify the strains of M. tuberculosis complex (MTC) and drug resistance patterns among the pulmonary tuberculosis patients. Methods: The study used a cross-sectional design, and 815 patients were recruited randomly in three study periods. In the first-period, 210 treated PTB patients, who were completed their treatment, received their diagnoses using light microscopy, fluorescence microscopy and cultured on Lowenstein-Jensen (L-J) slant, and then strains were identified as MTC by biochemical tests, and then sensitivity test in National Institute of Diseases of the Chest and Hospital. In the second-period, 220 re-treated PTB patients, who were completed their treatment, received their diagnoses using culture on L-J slant, line probe assay (LPA), and GeneXpert in the same hospital. In the last-period, during treatment, 385 MDR-PTB patients received their diagnoses using culture on L-J slant and LPA in the same hospital. Results: Among sixty-two (29.5%) PTB patients, 13% were sensitive to all first-line anti-TB drugs, 26% were MDR-TB patients, and 14.2% were pre-XDR-TB among 14 MDR-TB patients. After three years, 31% were MDR-TB among 220 re-treated PTB patients. After five years, 16.4% was pre-XDR-TB among 385 MDR-TB patients. Compared to females, male patients were significantly higher at all times. Conclusion: The current study demonstrated that in three study periods, the proportions of DR-TB, MDR-TB, and pre-XDR patients were an alarming issue and increasing daily.

Keywords: multi-drug resistant, drug-resistant, pre-extensive drug resistant, pulmonary tuberculosis

Procedia PDF Downloads 49