Search results for: feed selection

Authors: Thamer Alshuwaili, Yonglin Ren, Bob Du, Manjree Agarwal

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The warehouse beetle, Trogoderma variabile Ballion (Coleoptera: Dermestidae), is a major pest of packaged and processed stored products. Warehouse beetle is the common name which was given by Okumura (1972). This pest has been reported to infest 119 different commodities, and it is distributed throughout the tropical and subtropical parts of the world. Also, it is difficult to control because of the insect's ability to stay without food for long times, and it can survive for years under dry conditions and low-moisture food, and it has also developed resistance to many insecticides. The young larvae of these insects can cause damage to seeds, but older larvae prefer to feed on whole grains. The percentage of damage caused by these insects range between 30-70% in the storage. T. variabile is the species most responsible for causing significant damage in grain stores worldwide. Trogoderma spp. is a huge problem for cereal grains, and there are many countries, such as the USA, Australia, China, Kenya, Uganda and Tanzania who have specific quarantine regulations against possible importation. Also, grain stocks can be almost completely destroyed because of the massive populations the insect may develop. However, the purpose of the current research was to optimize conditions to collect volatile organic compound from Trogoderma variabile at different life stages by using headspace solid phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS) and flame ionization detection (FID). Using SPME technique to extract volatile from insects is an efficient, straightforward and nondestructive method. Result of the study shows that 15 insects were optimal number for larvae and adults. Selection of the number of insects depend on the height of the peak area and the number of peaks. Sixteen hours were optimized as the best extraction time for larvae and 8 hours was the optimal number of adults.

Keywords: Trogoderma variabile, warehouse beetle , GC-MS, Solid phase microextraction

Procedia PDF Downloads 110

Authors: Welder A. Baldassini, Jon J. Ramsey, Marcos R. Chiaratti, Amália S. Chaves, Renata H. Branco, Sarah F. M. Bonilha, Dante P. D. Lanna

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With increased production costs there is a need for animals that are more efficient in terms of meat production. In this context, the role of mitochondrial DNA (mtDNA) on physiological processes in liver, muscle and adipose tissues may account for inter-animal variation in energy expenditures and heat production. The purpose this study was to investigate if the amounts of mtDNA in liver, muscle and adipose tissue (subcutaneous and visceral depots) of Nellore bulls are associated with residual feed intake (RFI) and estimated heat production (EHP). Eighteen animals were individually fed in a feedlot for 90 days. RFI values were obtained by regression of dry matter intake (DMI) in relation to average daily gain (ADG) and mid-test metabolic body weight (BW). The animals were classified into low (more efficient) and high (less efficient) RFI groups. The bulls were then randomly distributed in individual pens where they were given excess feed twice daily to result in 5 to 10% orts for 90 d with diet containing 15% crude protein and 2.7 Mcal ME/kg DM. The heart rate (HR) of bulls was monitored for 4 consecutive days and used for calculation of EHP. Electrodes were fitted to bulls with stretch belts (POLAR RS400; Kempele, Finland). To calculate oxygen pulse (O2P), oxygen consumption was obtained using a facemask connected to the gas analyzer (EXHALYZER, ECOMedics, Zurich, Switzerland) and HR were simultaneously measured for 15 minutes period. Daily oxygen (O2) consumption was calculated by multiplying the volume of O2 per beat by total daily beats. EHP was calculated multiplying O2P by the average HR obtained during the 4 days, assuming 4.89 kcal/L of O2 to measure daily EHP that was expressed in kilocalories/day/kilogram metabolic BW (kcal/day/kg BW0.75). Blood samples were collected between days 45 and 90th after the beginning of the trial period in order to measure the concentration of hemoglobin and hematocrit. The bulls were slaughtered in an experimental slaughter house in accordance with current guidelines. Immediately after slaughter, a section of liver, a portion of longissimus thoracis (LT) muscle, plus a portion of subcutaneous fat (surrounding LT muscle) and portions of visceral fat (kidney, pelvis and inguinal fat) were collected. Samples of liver, muscle and adipose tissues were used to quantify mtDNA copy number per cell. The number of mtDNA copies was determined by normalization of mtDNA amount against a single copy nuclear gene (B2M). Mean of EHP, hemoglobin and hematocrit of high and low RFI bulls were compared using two-sample t-tests. Additionally, the one-way ANOVA was used to compare mtDNA quantification considering the mains effects of RFI groups. We found lower EHP (83.047 vs. 97.590 kcal/day/kgBW0.75; P < 0.10), hemoglobin concentration (13.533 vs. 15.108 g/dL; P < 0.10) and hematocrit percentage (39.3 vs. 43.6 %; P < 0.05) in low compared to high RFI bulls, respectively, which may be useful traits to identify efficient animals. However, no differences were observed between the mtDNA content in liver, muscle and adipose tissue of Nellore bulls with high and low RFI.

Keywords: bioenergetics, Bos indicus, feed efficiency, mitochondria

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Authors: Guilhermina Torrao

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An extensive number of studies have been conducted to determine the factors which influence crash injury risk (CIR); however, uncertainties inherent to selected variables have been neglected. A review of existing literature is required to not only obtain an overview of the variables and measures but also ascertain the implications when comparing studies without a systematic view of variable taxonomy. Therefore, the aim of this literature review is to examine and report on peer-reviewed studies in the field of crash analysis and to understand the implications of broad variations in variable selection in CIR analysis. The objective of this study is to demonstrate the variance in variable selection and classification when modeling injury risk involving occupants of light vehicles by presenting an analytical review of the literature. Based on data collected from 64 journal publications reported over the past 21 years, the analytical review discusses the variables selected by each study across an organized list of predictors for CIR analysis and provides a better understanding of the contribution of accident and vehicle factors to injuries acquired by occupants of light vehicles. A cross-comparison analysis demonstrates that almost half the studies (48%) did not consider vehicle design specifications (e.g., vehicle weight), whereas, for those that did, the vehicle age/model year was the most selected explanatory variable used by 41% of the literature studies. For those studies that included speed risk factor in their analyses, the majority (64%) used the legal speed limit data as a ‘proxy’ of vehicle speed at the moment of a crash, imposing limitations for CIR analysis and modeling. Despite the proven efficiency of airbags in minimizing injury impact following a crash, only 22% of studies included airbag deployment data. A major contribution of this study is to highlight the uncertainty linked to explanatory variable selection and identify opportunities for improvements when performing future studies in the field of road injuries.

Keywords: crash, exploratory, injury, risk, variables, vehicle

Procedia PDF Downloads 115

Authors: Rajesha Kumar Alambi, Mansour Ahmed, Garudachari Bhadrachari, Safiyah Al-Muqahwi, Mansour Al-Rughaib, Jibu P. Thomas

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Membrane-based pressure assisted osmosis (PAO) for seawater desalination has the potential to overcome the challenges of forward osmosis technology. PAO technology is gaining interest among the research community to ensure the sustainability of freshwater with a significant reduction in energy. The requirements of PAO membranes differ from the FO membrane; as it needs a slightly higher porous with sufficient mechanical strength to overcome the applied hydraulic pressure. The porous metal-organic framework (MOF) as a filler for the membrane synthesis has demonstrated a great potential to generate new channels for water transport, high selectivity, and reduced fouling propensity. Accordingly, this study is aimed at fabricating the UiO-66 MOF-based thin film nanocomposite membranes with specific characteristics for water desalination by PAO. A PAO test unit manufactured by Trevi System, USA, was used to determine the performance of the synthesized membranes. Further, the synthesized membranes were characterized in terms of morphological features, hydrophilicity, surface roughness, and mechanical properties. The 0.05 UiO-66 loaded membrane produced highest flux of 38L/m2h and with low reverse salt leakage of 2.1g/m²h for the DI water as feed solution and 2.0 M NaCl as draw solutions at the inlet feed pressure of 0.6 MPa. The new membranes showed a good tolerance toward the applied hydraulic pressure attributed to the fabric support used during the membrane synthesis.

Keywords: metal organic framework, composite membrane, desalination, salt rejection, flux

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Authors: Gaafar Omer BaOmer, Abdulmohsin A. Al-Sofyani, Hassan A. Ramadan

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Drupella is found on coral reefs throughout the tropical and subtropical shallow waters of the Indo-Pacific region. Drupella is muricid gastropod, obligate corallivorous and their population outbreak can cause significant coral mortality. Belt transect surveys were conducted at two sites (Bohairat and Baydah) in Jeddah coast, Saudi Arabia to assess prey preferences for D. cornus with respect to prey availability through resource selection ratios. Results revealed that there are different levels of prey preferences at the different age stages and at the different sites. Acropora species with a caespitose, corymbose and digitate growth forms were preferred prey for recruits and juveniles of Drupella cornus, whereas Acropora variolosa was avoided by D. cornus because of its arborescent colony growth form. Pocillopora, Stylophora, and Millipora were occupied by Drupella cornus less than expected, whereas massive corals genus Porites were avoided. High densities of D. cornus were observed on two fragments of Pocillopora damicornis which may because of the absence of coral guard crabs genus Trapezia. Mean densities of D. cornus per colony for each species showed significant differentiation between the two study sites. Low availability of Acropora colonies in Bayadah patch reef caused high mean density of D. cornus per colony to compare to that in Bohairat, whereas higher mean density of D. cornus per colony of Pocillopora in Bohairat than that in Bayadah may because of most of occupied Pocillopora colonies by D. cornus were physical broken by anchoring compare to those colonies in Bayadah. The results indicated that prey preferences seem to depend on both coral genus and colony shape, while mean densities of D. cornus depend on availability and status of coral colonies.

Keywords: prey availability, resource selection, Drupella cornus, Jeddah, Saudi Arabia

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Authors: Abdullah Al Farwan, Ya Zhang

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In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

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Authors: Chetan Mahawar, Sarath Chandran, Sridhar Panigrahi, V. P. Shaji

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The ever-growing advancement in space exploration has led to an alarming concern for space debris removal as it restricts further launch operations and adventurous space missions; hence numerous studies have come up with technologies for re-entry predictions and material selection processes for mitigating space debris. The selection of material and operating conditions is determined with the objective of lightweight structure and ability to demise faster subject to spacecraft survivability during its mission. Since the demisability of spacecraft depends on evolving thermal material properties such as emissivity, specific heat capacity, thermal conductivity, radiation intensity, etc. Therefore, this paper presents the analysis of evolving thermal material properties of spacecraft, which affect the demisability process and thus estimate demise time using the demisability model by incorporating evolving thermal properties for sensible heating followed by the complete or partial break-up of spacecraft. The demisability analysis thus concludes the best suitable spacecraft material is based on the least estimated demise time, which fulfills the criteria of design-for-survivability and as well as of design-for-demisability.

Keywords: demisability, emissivity, lightweight, re-entry, survivability

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Authors: Banca Patricia Pena Revuelta, Ramiro Gonzalez Avalos, Juan Leonardo Rocha Valdez, Jose Gonzalez Avalos, Karla Rodriguez Hernandez

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Probiotics are a promising alternative to improve productivity and animals' health. In addition, they can be part of the composition of different types of products, including foods (functional foods), medicines, and dietary supplements. The objective of the present work was to evaluate the effect of the feeding of Holstein calves supplemented with bacillus subtilis PB6 in morbidity and mortality. 60 newborn animals were used, randomly included in 1 of 3 treatments. The treatments were as follows: T1 = control, T2 = 10 g / calf / day. The first takes within 20 min after birth, T3 = 10 g / calf/day. The first takes between 12 and 24 h after birth. In all the treatments, 432 L of pasteurized whole milk divided into two doses/day 07:00 and 15:00, respectively, were given for 60 days. The addition of bacillus subtilis PB6 was carried out in the milk tub at the time of feeding them. The first colostrum intake (2 L • intake) was given within 2 h after birth, after which they were given a second 6 h after the first one. The diseases registered to monitor the morbidity and mortality of the calves were: diarrhea and pneumonia. The registry was carried out from birth to 60 days of life. The parameter evaluated was food consumption. The variable statistical analysis was performed using analysis of variance, and comparison of means was performed using the Tukey test. The value of P < 0.05 was used to consider the statistical difference. The results of the present study in relation to the consumption of food show no statistical difference P < 0.05 between treatments (14,762, 11,698, and 12,403 kg of food average, respectively). Calves group to which they were not provided Bacillus subtilis PB6 obtained higher feed intake. The addition of Bacillus subtilis PB6 in feeding calves does not increase feed intake.

Keywords: feeding, development, milk, probiotic

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Authors: Je-Seok Shin, Wook-Won Kim, Jin-O Kim

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The offshore wind farm needs to be designed carefully considering economics and reliability aspects. There are many decision-making problems for designing entire offshore wind farm, this paper focuses on an inner grid layout which means the connection between wind turbines as well as between wind turbines and an offshore substation. A methodology proposed in this paper determines the connections and the cable type for each connection section using K-clustering, minimum spanning tree and cable selection algorithms. And then, a cost evaluation is performed in terms of investment, power loss and reliability. Through the cost evaluation, an optimal layout of inner grid is determined so as to have the lowest total cost. In order to demonstrate the validity of the methodology, the case study is conducted on 240MW offshore wind farm, and the results show that it is helpful to design optimally offshore wind farm.

Keywords: offshore wind farm, optimal layout, k-clustering algorithm, minimum spanning algorithm, cable type selection, power loss cost, reliability cost

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Authors: Venkata Ramanaiah, Shabina Khanam

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Enormous potential for saving energy is available in coal-based sponge iron plants as these are associated with the high percentage of energy wastage per unit sponge iron production. An energy integration option is proposed, in the present paper, to a coal based sponge iron plant of 100 tonnes per day production capacity, being operated in India using SL/RN (Stelco-Lurgi/Republic Steel-National Lead) process. It consists of the rotary kiln, rotary cooler, dust settling chamber, after burning chamber, evaporating cooler, electrostatic precipitator (ESP), wet scrapper and chimney as important equipment. Principles of process integration are used in the proposed option. It accounts for preheating kiln inlet streams like kiln feed and slinger coal up to 170ᴼC using waste gas exiting ESP. Further, kiln outlet stream is cooled from 1020ᴼC to 110ᴼC using kiln air. The working areas in the plant where energy is being lost and can be conserved are identified. Detailed material and energy balances are carried out around the sponge iron plant, and a modified model is developed, to find coal requirement of proposed option, based on hot utility, heat of reactions, kiln feed and air preheating, radiation losses, dolomite decomposition, the heat required to vaporize the coal volatiles, etc. As coal is used as utility and process stream, an iterative approach is used in solution methodology to compute coal consumption. Further, water consumption, operating cost, capital investment, waste gas generation, profit, and payback period of the modification are computed. Along with these, operational aspects of the proposed design are also discussed. To recover and integrate waste heat available in the plant, three gas-solid heat exchangers and four insulated ducts with one FD fan for each are installed additionally. Thus, the proposed option requires total capital investment of $0.84 million. Preheating of kiln feed, slinger coal and kiln air streams reduce coal consumption by 24.63% which in turn reduces waste gas generation by 25.2% in comparison to the existing process. Moreover, 96% reduction in water is also observed, which is the added advantage of the modification. Consequently, total profit is found as $2.06 million/year with payback period of 4.97 months only. The energy efficient factor (EEF), which is the % of the maximum energy that can be saved through design, is found to be 56.7%. Results of the proposed option are also compared with literature and found in good agreement.

Keywords: coal consumption, energy conservation, process integration, sponge iron plant

Procedia PDF Downloads 132

Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

Procedia PDF Downloads 100

Authors: Irina Khutsishvili

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In the present research, a decision support methodology for the multi-attribute group decision-making (MAGDM) problem is developed, namely for the selection of investment projects. The objective of the investment project selection problem is to choose the best project among the set of projects, seeking investment, or to rank all projects in descending order. The project selection is made considering a set of weighted attributes. To evaluate the attributes in our approach, expert assessments are used. In the proposed methodology, lingual expressions (linguistic terms) given by all experts are used as initial attribute evaluations, since they are the most natural and convenient representation of experts' evaluations. Then lingual evaluations are converted into trapezoidal fuzzy numbers, and the aggregate trapezoidal hesitant fuzzy decision matrix will be built. The case is considered when information on the attribute weights is completely unknown. The attribute weights are identified based on the De Luca and Termini information entropy concept, determined in the context of hesitant fuzzy sets. The decisions are made using the extended Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method under a hesitant fuzzy environment. Hence, a methodology is based on a trapezoidal valued hesitant fuzzy TOPSIS decision-making model with entropy weights. The ranking of alternatives is performed by the proximity of their distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). For this purpose, the weighted hesitant Hamming distance is used. An example of investment decision-making is shown that clearly explains the procedure of the proposed methodology.

Keywords: In the present research, a decision support methodology for the multi-attribute group decision-making (MAGDM) problem is developed, namely for the selection of investment projects. The objective of the investment project selection problem is to choose the best project among the set of projects, seeking investment, or to rank all projects in descending order. The project selection is made considering a set of weighted attributes. To evaluate the attributes in our approach, expert assessments are used. In the proposed methodology, lingual expressions (linguistic terms) given by all experts are used as initial attribute evaluations since they are the most natural and convenient representation of experts' evaluations. Then lingual evaluations are converted into trapezoidal fuzzy numbers, and the aggregate trapezoidal hesitant fuzzy decision matrix will be built. The case is considered when information on the attribute weights is completely unknown. The attribute weights are identified based on the De Luca and Termini information entropy concept, determined in the context of hesitant fuzzy sets. The decisions are made using the extended Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method under a hesitant fuzzy environment. Hence, a methodology is based on a trapezoidal valued hesitant fuzzy TOPSIS decision-making model with entropy weights. The ranking of alternatives is performed by the proximity of their distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). For this purpose, the weighted hesitant Hamming distance is used. An example of investment decision-making is shown that clearly explains the procedure of the proposed methodology.

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Authors: Aitor Bilbao, Dragos Axinte, John Billingham

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The inverse problem in Energy Beam (EB) Processes consists of defining the control parameters, in particular the 2D beam path (position and orientation of the beam as a function of time), to arrive at a prescribed solution (freeform surface). This inverse problem is well understood for conventional machining, because the cutting tool geometry is well defined and the material removal is a time independent process. In contrast, EB machining is achieved through the local interaction of a beam of particular characteristics (e.g. energy distribution), which leads to a surface-dependent removal rate. Furthermore, EB machining is a time-dependent process in which not only the beam varies with the dwell time, but any acceleration/deceleration of the machine/beam delivery system, when performing raster paths will influence the actual geometry of the surface to be generated. Two different EB processes, Abrasive Water Machining (AWJM) and Pulsed Laser Ablation (PLA), are studied. Even though they are considered as independent different technologies, both can be described as time-dependent processes. AWJM can be considered as a continuous process and the etched material depends on the feed speed of the jet at each instant during the process. On the other hand, PLA processes are usually defined as discrete systems and the total removed material is calculated by the summation of the different pulses shot during the process. The overlapping of these shots depends on the feed speed and the frequency between two consecutive shots. However, if the feed speed is sufficiently slow compared with the frequency, then consecutive shots are close enough and the behaviour can be similar to a continuous process. Using this approximation a generic continuous model can be described for both processes. The inverse problem is usually solved for this kind of process by simply controlling dwell time in proportion to the required depth of milling at each single pixel on the surface using a linear model of the process. However, this approach does not always lead to the good solution since linear models are only valid when shallow surfaces are etched. The solution of the inverse problem is improved by using a discrete adjoint optimization algorithm. Moreover, the calculation of the Jacobian matrix consumes less computation time than finite difference approaches. The influence of the dynamics of the machine on the actual movement of the jet is also important and should be taken into account. When the parameters of the controller are not known or cannot be changed, a simple approximation is used for the choice of the slope of a step profile. Several experimental tests are performed for both technologies to show the usefulness of this approach.

Keywords: abrasive waterjet machining, energy beam processes, inverse problem, pulsed laser ablation

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Authors: Kudzanayi Chiteka, Wellington Makondo

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The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.

Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models

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Authors: Eng. M. Ahmed, A. Ibrahim, M. Ashour

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One of the major concerns facing dam is the repair of their structures to prevent the seepage under them. In previous years, many existing dams have been treated by grouting, but with varying degrees of success. One of the major reasons for this erratic performance is the unsuitable selection of the grouting materials to reduce the seepage. Grouting is an effective way to improve the engineering properties of the soil and strengthen of the permeability of the soil to reduce the seepage. The purpose of this paper is to focus on the efficiency of current available grouting materials and techniques from construction, environmental and economical point of view. The seepage reduction usually accomplished by either chemical grouting or cementious grouting using ultrafine cement. In addition, the study shows a comparison between grouting materials according to their degree of permeability reduction and cost. The application of seepage reduction is based on the permeation grouting using grout curtain installation. The computer program (SEEP/W) is employed to model a dam rested on sandy soil, using grout curtain to reduce seepage quantity and hydraulic gradient by different grouting materials. This study presents a relationship that takes into account the permeability of the soil, grout curtain spacing and a new performance parameter that can be used to predict the best selection of grouting materials for seepage reduction.

Keywords: seepage, sandy soil, grouting, permeability

Procedia PDF Downloads 349

Authors: Lucretia Ramnath

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Fishmeal is extensively used for fish farming but is an expensive fish feed ingredient. A cheaper alternate to fishmeal is single cell protein (SCP) which can be cultivated on fermentable sugars recovered from organic waste streams such as pulp and paper mill sludge (PPMS). PPMS has a high cellulose content, thus is suitable for glucose recovery through enzymatic hydrolysis but is hampered by lignin and ash. To render PPMS amenable for enzymatic hydrolysis, the PPMS waspre-treated to produce a glucose-rich hydrolysate which served as a feed stock for the production of fungal SCP. The PPMS used in this study had the following composition: 72.77% carbohydrates, 8.6% lignin, and 18.63% ash. The pre-treatments had no significant effect on lignin composition but had a substantial effect on carbohydrate and ash content. Enzymatic hydrolysis of screened PPMS was previously optimized through response surface methodology (RSM) and 2-factorial design. The optimized protocol resulted in a hydrolysate containing 46.1 g/L of glucose, of which 86% was recovered after downstream processing by passing through a 100-mesh sieve (38 µm pore size). Vogel’s medium supplemented with 10 g/L hydrolysate successfully supported the growth of Fusarium venenatum, conducted using standard growth conditions; pH 6, 200 rpm, 2.88 g/L ammonium phosphate, 25°C. A maximum F. venenatum biomass of 45 g/L was produced with a yield coefficient of 4.67. Pulp and paper mill sludge hydrolysate contained approximately five times more glucose than what was needed for SCP production and served as a suitable carbon source. We have shown that PPMS can be successfully beneficiated for SCP production.

Keywords: pulp and paper waste, fungi, single cell protein, hydrolysate

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Authors: Rupita Ghosh, Ritwik Sarkar, Sumit K. Pal, Soumitra Paul

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The use of Hydroxyapatite bioceramics as restorative implants is widely known. These materials can be manufactured by pressing and sintering route to a particular shape. However machining processes are still a basic requirement to give a near net shape to those implants for ensuring dimensional and geometrical accuracy. In this context, optimising the machining parameters is an important factor to understand the machinability of the materials and to reduce the production cost. In the present study a method has been optimized to produce true particulate drilled composite of Hydroxyapatite Yttrium Phosphate. The phosphates are used in varying ratio for a comparative study on the effect of flexural strength, hardness, machining (drilling) parameters and bioactivity.. The maximum flexural strength and hardness of the composite that could be attained are 46.07 MPa and 1.02 GPa respectively. Drilling is done with a conventional radial drilling machine aided with dynamometer with high speed steel (HSS) and solid carbide (SC) drills. The effect of variation in drilling parameters (cutting speed and feed), cutting tool, batch composition on torque, thrust force and tool wear are studied. It is observed that the thrust force and torque varies greatly with the increase in the speed, feed and yttrium phosphate content in the composite. Significant differences in the thrust and torque are noticed due to the change of the drills as well. Bioactivity study is done in simulated body fluid (SBF) upto 28 days. The growth of the bone like apatite has become denser with the increase in the number of days for all the composition of the composites and it is comparable to that of the pure hydroxyapatite.

Keywords: Bioactivity, Drilling, Hydroxyapatite, Yttrium Phosphate

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Authors: Tamirat Solomon, Aberash Yohannis, Efrem Gulfo

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The plantation of trees, which harmonizes the agroecology of the environment, has been implemented in Ethiopia with great concern for a noticeably degraded environment. This study was designed to evaluate the effectiveness of green legacy, species selection and, the rate of survival, and the management status in the study areas. A systematic sampling method was employed to collect the required data from 144 quadrants measuring a 15m radius with an interval of 40m apart. Additionally, 244 sample households were selected for the socioeconomic study in addition to secondary data collected from office recordings. The data collected was analyzed using multivariate analysis, considering exposure and outcome variables. The findings of this study indicated that four exotic tree species, namely; A. salgina, C. fistula, A. indica, and G. robusta, were commonly selected tree species for degraded land restoration in the study areas. Among the seedlings planted at the four study sites, a total of 79.9% survived, and A. salgina was the dominant and best performed species, A. indica was the least survived species in the entire study area. The age of the seedling before planting significantly (p = 0.05) affected the survival potential of most seedlings of species, and the majority (82%) of local communities expressed their positive attitudes and willingness to manage the restoration works in the study areas. It was recommended to consider the inclusion of native species in the restoration effort and evaluate the co-existence of native flora with exotic and its competition for nutrients, water, and light in addition to the invading potentials in the ecosystem. In general, before embarking on degraded land restoration, species selection, adequate preparation of seedlings, and species diversity composition that exactly fit the socioeconomic and ecological demands of the areas must get the attention for the success of the restoration.

Keywords: plantation forest, degraded land, forest restoration, plantation survival, species selection

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Authors: Sayyed Benyamin Alavi, Giovanni Cerri, Leila Chennaoui, Ambra Giovannelli, Stefano Mazzoni

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Primary energy consumption and emissions of pollutants (including CO2) sustainability call to search methodologies to lower power absorption for unit of a given product. Cool production plants based on vapour compression are widely used for many applications: air conditioning, food conservation, domestic refrigerators and freezers, special industrial processes, etc. In the field of cool production, the amount of Yearly Consumed Primary Energy is enormous, thus, saving some percentage of it, leads to big worldwide impact in the energy consumption and related energy sustainability. Among various techniques to reduce power required by a Vapour Compression Cool Production Plant (VCCPP), the technique based on Power Regeneration by means of Internal Direct Cycle (IDC) will be considered in this paper. Power produced by IDC reduces power need for unit of produced Cool Power by the VCCPP. The paper contains basic concepts that lead to develop IDCs and the proposed options to use the IDC Power. Among various selections for using turbo machines, Best Economically Available Technologies (BEATs) have been explored. Based on vehicle engine turbochargers, they have been taken into consideration for this application. According to BEAT Database and similarity rules, the best turbo machine selection leads to the minimum nominal power required by VCCPP Main Compressor. Results obtained installing the prototype in “ad hoc” designed test bench will be discussed and compared with the expected performance. Forecasts for the upgrading VCCPP, various applications will be given and discussed. 4-6% saving is expected for air conditioning cooling plants and 15-22% is expected for cryogenic plants.

Keywords: Refrigeration Plant, Vapour Pressure Amplifier, Compressor, Expander, Turbine, Turbomachinery Selection, Power Saving

Procedia PDF Downloads 414

Authors: Imed Feki, Faouzi Msahli

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Selection of relevant parameters from a high dimensional process operation setting space is a problem frequently encountered in industrial process modelling. This paper presents a method for selecting the most relevant fabric physical parameters for each sensory quality feature. The proposed relevancy criterion has been developed using two approaches. The first utilizes a fuzzy sensitivity criterion by exploiting from experimental data the relationship between physical parameters and all the sensory quality features for each evaluator. Next an OWA aggregation procedure is applied to aggregate the ranking lists provided by different evaluators. In the second approach, another panel of experts provides their ranking lists of physical features according to their professional knowledge. Also by applying OWA and a fuzzy aggregation model, the data sensitivity-based ranking list and the knowledge-based ranking list are combined using our proposed percolation technique, to determine the final ranking list. The key issue of the proposed percolation technique is to filter automatically and objectively the relevant features by creating a gap between scores of relevant and irrelevant parameters. It permits to automatically generate threshold that can effectively reduce human subjectivity and arbitrariness when manually choosing thresholds. For a specific sensory descriptor, the threshold is defined systematically by iteratively aggregating (n times) the ranking lists generated by OWA and fuzzy models, according to a specific algorithm. Having applied the percolation technique on a real example, of a well known finished textile product especially the stonewashed denims, usually considered as the most important quality criteria in jeans’ evaluation, we separate the relevant physical features from irrelevant ones for each sensory descriptor. The originality and performance of the proposed relevant feature selection method can be shown by the variability in the number of physical features in the set of selected relevant parameters. Instead of selecting identical numbers of features with a predefined threshold, the proposed method can be adapted to the specific natures of the complex relations between sensory descriptors and physical features, in order to propose lists of relevant features of different sizes for different descriptors. In order to obtain more reliable results for selection of relevant physical features, the percolation technique has been applied for combining the fuzzy global relevancy and OWA global relevancy criteria in order to clearly distinguish scores of the relevant physical features from those of irrelevant ones.

Keywords: data sensitivity, feature selection, fuzzy logic, OWA operators, percolation technique

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Authors: Piotr Ciuman, Barbara Lipska

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The aim of presented research was to improve numerical predictions of air parameters distribution in the actual natatorium by the selection of calculation formula of mass flux of moisture emitted from the pool. Selected correlation should ensure the best compliance of numerical results with the measurements' results of these parameters in the facility. The numerical model of the natatorium was developed, for which boundary conditions were prepared on the basis of measurements' results carried out in the actual facility. Numerical calculations were carried out with the use of ANSYS CFX software, with six formulas being implemented, which in various ways made the moisture emission dependent on water surface temperature and air parameters in the natatorium. The results of calculations with the use of these formulas were compared for air parameters' distributions: Specific humidity, velocity and temperature in the facility. For the selection of the best formula, numerical results of these parameters in occupied zone were validated by comparison with the measurements' results carried out at selected points of this zone.

Keywords: experimental validation, indoor swimming pool, moisture emission, natatorium, numerical calculations CFD, thermal and humidity conditions, ventilation

Procedia PDF Downloads 390

Authors: Bachir Bentouati, Lakhdar Chaib, Saliha Chettih, Gai-Ge Wang

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The problem of economic dispatch (ED) is the basic problem of power framework, its main goal is to find the most favorable generation dispatch to generate each unit, reduce the whole power generation cost, and meet all system limitations. A heuristic algorithm, recently developed called Stud Krill Herd (SKH), has been employed in this paper to treat non-convex ED problems. The proposed KH has been modified using Stud selection and crossover (SSC) operator, to enhance the solution quality and avoid local optima. We are demonstrated SKH effects in two case study systems composed of 13-unit and 40-unit test systems to verify its performance and applicability in solving the ED problems. In the above systems, SKH can successfully obtain the best fuel generator and distribute the load requirements for the online generators. The results showed that the use of the proposed SKH method could reduce the total cost of generation and optimize the fulfillment of the load requirements.

Keywords: stud krill herd, economic dispatch, crossover, stud selection, valve-point effect

Procedia PDF Downloads 185

Authors: Da Yoon Yu, Jeong A. Kim, In Sung Kim, Yeon Hee Hong, Jae Young Kim, Sang Suk Lee, Sung Chan Kim, So Hui Choe, In Soon Choi, Kwang Keun Cho

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The present study was conducted to identify the effects of synbiotics composed of lactic acid (LA) bacteria (LAB) and sea tangle on rat’s intestinal microorganisms and anti-obesity effects. The experiment was conducted for six weeks using an 8-week old male rat as experiment animals and the experimental design was to use six treatments groups of 4 repetitions using three mice per repetition. The treatment groups were organized into a normal fat diet control (NFC), a high fat (HF) diet control (HFC), a prebiotic 0% treatment (HF+LA+sea tangle 0%, ST0), a prebiotic 5% treatment (HF+LA+sea tangle 5%, ST5), a prebiotic 10% treatment (HF+LA+sea tangle 10%, ST10), and a prebiotic 15% treatment group (HF+LA+sea tangle 15%, ST15) to conduct experiments with various levels of prebiotics. According to the results of the experiment, the NFC group showed the highest daily weight gain (22.34g) and the ST0 group showed the lowest daily weight gain (19.41g). However, weight gains during the entire experimental period were the highest in the HFC group (475.73g) and the lowest in the ST0 group (454.23g). Feed efficiency was the highest in the HFC group (0.20). Treatment with synbiotics composed of LAB and sea tangle suppressed weight increases due to HF diet and reduced feed efficiency. Intestinal microorganisms were identified through pyrosequncing and according to the results, Firmicutes phylum (approximately 60%) and Bacteroidetes phylum (approximately 30%) accounted for approximately 90% or more of intestinal microorganisms in all of the treatment groups indicating these bacteria are dominating in the intestines. Firmicutes that is related to weight increases accounted for 64.96% of microorganisms in the NFC group, 75.32% in the HFC group, 59.51% in the ST0 group, 61.29% in the ST5 group, 49.91% in the ST10 group, and 39.65% in the ST15 group. Therefore, Firmicutes showed the highest share the HFC group that showed high weight gains and the lowest share in the group treated with mixed synbiotics composed of LAB and sea tangle. Bacteroidetes that is related to weight gain inhibition accounted for 32.12% of microorganisms in the NFC group, and HFC group 21.57%, ST0 group 37.66%, ST5 group 34.92%, ST10 group 44.46%, and ST15 group 53.22%. Therefore, the share of Bacteroidetes was the lowest in the HFC group with no addition of synbiotics and increased along with the level of treatment with synbiotics. Changes in blood components were not significantly different among the groups and SCFA yields were shown to be higher in groups treated with synbiotics than in groups not added with synbiotics. Through the present study, it was shown that the supply of synbiotics composed of LAB and sea tangle increased feed intake but led to weight losses and that the intake of synbiotics composed of LAB and sea tangle had anti-obesity effects due to decreases in Firmicutes which are microorganisms related to weight gains and increases in Bacteroidetes which are microorganisms related to weight losses. Therefore, synbiotics composed of LAB and sea tangle are considered to have the effect to prevent metabolic disorders in the rat.

Keywords: bacteroidetes, firmicutes, intestinal microbiota, lactic acid, sea tangle, synbiotics

Procedia PDF Downloads 386

Authors: Erico Da Silva Lima, Tiago Neves Pereira Valente, Roberto De Oliveira Roça

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Introduction: Over the last few years the market has increased its demand for high quality meat. Based on this premise some producers have continuously improved their efficiency in breeding beef cattle with the purpose to support this demand. It is well recognized that final quality of beef is intimately linked to animal’s diet. The key objective of this study is to evaluate the influence of feeding animals with cottonseed and its lipids and the final results in terms of pH and shear forces of the meat. Materials and Methods: The study was carried out in the Chapéu de Couro Farm in Aguaí/SP, Brazil. A group of 39 uncastrated Nellore cattle. Mean age of the animals was 36 months and initial mean live weight was 494.1 ± 10.1. Animals were randomly assigned to one of three treatments, based on dry matter: feed with control diet 2.50% cottonseed, feed with 11.50% cottonseed, and feed with 3.13% cottonseed added of 1.77% protected lipid. Forage:concentrate ratio was 50:50 on a dry matter basis. Sugar cane chopped was used as forage. After slaughter, carcasses were identified and divided into two halves that were kept in a cold chamber for 24 h at 2°C. Using pH meter was determined post-mortem pH in Longissimus thoracis muscle between the 12th and 13th rib of the left half carcass. After, part of each animal was removed, and divided in three samples (steaks). Steaks were 2.5 cm thick and were identified and stored individually in plastic bags under vacuum. Samples were frozen in a freezer at -18°C. The same samples cooked were refrigerated by 12 h the 4°C, and then cut into cylinders 1.10 Øcm with the support of a drill press avoiding fats and nerves. Shear force was calculated in these samples cut into cylinders through the Brookfield texture CT3 Texture Analyzer 25 k equipped with a set of blade Warner-Bratzler. Results and Discussion: No differences (P > 0.05) in pH 24 h after slaughter were observed in the meat of Nellore cattle fed different sources of fat, and mean value for this variable was 5.59. However, for the shear force differences (P < 0.05) were founded. For diet with 2,50% cottonseed the lowest value found 5.10 (kg) while for the treatment with 11.50% cottonseed the great value found was 6.30 (kg). High shear force values mean greater texture of meat that indicates less tenderness. The texture of the meat can be influenced by age, weight to the slaughter of animals. For cattle breed Nellore Bos taurus indicus more high value of shear force. Conclusions: The add the cottonseed or protected lipid in diet is not affected pH values in meat. The whole cottonseed does not contribute to the improvement of tenderness of the meat. Acknowledgments: IFGoiano, FAPEG and CNPq (Brazil).

Keywords: beef quality, cottonseed, protected fat, shear force

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Authors: Tamara Romero, Manuel Romero-Huelva, Jose V. Segarra, Jose Castro, Carlos Fernandez

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Many foods resulting from processing and manufacturing end up as waste, most of which is burned, dumped into landfills or used as compost, which leads to wasted resources, and environmental problems due to unsuitable disposal. Using residues of the crop and food processing industries to feed livestock has the advantage to obviating the need for costly waste management programs. The main residue generated in citrus cultivations and rice crop are pruning waste and rice straw, respectively. Within Spain, the Valencian Community is one of the world's oldest citrus and rice production areas. The objective of this experiment found out the effects of including orange leaves and rice straw as ingredients in the concentrate diets of goats, on milk production and methane (CH₄) emissions. Ten Murciano-Granadina dairy goats (45 kg of body weight, on average) in mid-lactation were selected in a crossover design experiment, where each goat received two treatments in 2 periods. Both groups were fed with 1.7 kg pelleted mixed ration; one group (n= 5) was a control (C) and the other group (n= 5) used orange leaves and rice straw (OR). The forage was alfalfa hay, and it was the same for the two groups (1 kg of alfalfa was offered by goat and day). The diets employed to achieve the requirements during lactation period for caprine livestock. The goats were allocated to individual metabolism cages. After 14 days of adaptation, feed intake and milk yield were recorded daily over a 5 days period. Physico-chemical parameters and somatic cell count in milk samples were determined. Then, gas exchange measurements were recorded individually by an open-circuit indirect calorimetry system using a head box. The data were analyzed by mixed model with diet and digestibility as fixed effect and goat as random effect. No differences were found for dry matter intake (2.23 kg/d, on average). Higher milk yield was found for C diet than OR (2.3 vs. 2.1 kg/goat and day, respectively) and, greater milk fat content was observed for OR than C (6.5 vs. 5.5%, respectively). The cheese extract was also greater in OR than C (10.7 vs. 9.6%). Goats fed OR diet produced significantly fewer CH₄ emissions than C diet (27 vs. 30 g/d, respectively). These preliminary results (LIFE Project LOWCARBON FEED LIFE/CCM/ES/000088) suggested that the use of these waste by-products was effective in reducing CH₄ emission without detrimental effect on milk yield.

Keywords: agricultural waste, goat, milk production, methane emission

Procedia PDF Downloads 129

Authors: Vilma Sasyte, Vilma Viliene, Agila Dauksiene, Asta Raceviciute-Stupeliene, Romas Gruzauskas, Saulius Alijosius

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The eight-week feeding trial was conducted involving 27-wk-old Isa brown laying hens to study the effect of dry extrusion processing on partial reduction in total glucosinolates content of locally produced rapeseed and on productivity and eggs quality parameters of laying hens. Thirty-six hens were randomly assigned one of three treatments (CONTR, AERS and HERS), each comprising 12, individual caged layers. The main composition of the diets was the same, but extruded soya bean seed were replaced with 2.5% of the extruded rapeseed in the AERS group and 4.5 % in the HERS group. Rapeseed was extruded together with faba beans. Due to extrusion process the glucosinolates content was reduced by 7.83 µmol/g of rapeseed. The results of conducted trial shows, that during all experimental period egg production parameters, such as the average feed intake (6529.17 vs. 6257 g/hen/14 day; P < 0.05) and laying intensity (94.35% vs. 89.29; P < 0.05) were statistically different for HERS and CONTR laying hens respectively. Only the feed conversion ratio to produce 1 kg of eggs, kg in AERS group was by 11 % lower compared to CONTR group (P < 0.05). By analysing the effect of extruded rapeseed on egg mass, the statistical differences between treatments were no determined. The dietary treatments did not affect egg weight, albumen height, haugh units, albumen and yolk pH. However, in the HERS group were get eggs with the more intensive yolk color, higher redness (a) and yellowness (b) values. The inclusion of full-fat extruded rapeseed had no effect on egg shell quality parameters, i.e. shell breaking strength, shell weight with and without coat and shell index, but in the experimental groups were get eggs with the thinner shell (P < 0.05). The internal egg quality analysis showed that with higher content of extruded rapeseed (4.5 %) level in the diet, the total cholesterol in the eggs yolk decreased by 1.92 mg/g in comparison with CONTR group (P < 0.05). Eggs laid by hens fed the diet containing 2.5% and 4.5% had increasing ∑PNRR/∑SRR ratio and decreasing ∑(n-6)/∑(n-3) ratio values of eggs yolk fatty acids than in CONTR group. Eggs of hens fed different amount of extruded rapeseed presented an n-6 : n-3 ratio changed from 5.17 to 4.71. The analysis of the relationship between hypocholesteremia/ hypercholesterolemia fatty acids (H/H), which is based on the functional properties of fatty acids, found that the value of it ratio is significant higher in laying hens fed diets supplemented with 4.5% extruded rapeseed than the CONTR group, demonstrating the positive effects of extruded rapeseed on egg quality. The results of trial confirmed that extruded full fat rapeseed to the 4.5% are suitable to replace soyabean in the compound feed of laying hens.

Keywords: egg quality, extruded full-fat rapeseed, laying hens, productivity

Procedia PDF Downloads 200

Authors: Yung C. Lin, Kung D. Wu, Wei C. Shih, Jui P. Hung

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High speed and high precision machining have become the most important technology in manufacturing industry. The surface roughness of high precision components is regarded as the important characteristics of the product quality. However, machining chatter could damage the machined surface and restricts the process efficiency. Therefore, selection of the appropriate cutting conditions is of importance to prevent the occurrence of chatter. In addition, vibration of the spindle tool also affects the surface quality, which implies the surface precision can be controlled by monitoring the vibration of the spindle tool. Based on this concept, this study was aimed to investigate the influence of the machining conditions on the surface roughness and the vibration of the spindle tool. To this end, a series of machining tests were conducted on aluminum alloy. In tests, the vibration of the spindle tool was measured by using the acceleration sensors. The surface roughness of the machined parts was examined using white light interferometer. The response surface methodology (RSM) was employed to establish the mathematical models for predicting surface finish and tool vibration, respectively. The correlation between the surface roughness and spindle tool vibration was also analyzed by ANOVA analysis. According to the machining tests, machined surface with or without chattering was marked on the lobes diagram as the verification of the machining conditions. Using multivariable regression analysis, the mathematical models for predicting the surface roughness and tool vibrations were developed based on the machining parameters, cutting depth (a), feed rate (f) and spindle speed (s). The predicted roughness is shown to agree well with the measured roughness, an average percentage of errors of 10%. The average percentage of errors of the tool vibrations between the measurements and the predictions of mathematical model is about 7.39%. In addition, the tool vibration under various machining conditions has been found to have a positive influence on the surface roughness (r=0.78). As a conclusion from current results, the mathematical models were successfully developed for the predictions of the surface roughness and vibration level of the spindle tool under different cutting condition, which can help to select appropriate cutting parameters and to monitor the machining conditions to achieve high surface quality in milling operation.

Keywords: machining parameters, machining stability, regression analysis, surface roughness

Procedia PDF Downloads 216

Authors: Muhammad Adeel Arshad, Faiz-Ul Hassan, Yanfen Cheng

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According to FAO, enteric methane (CH4) production is about 44% of all greenhouse gas emissions from the livestock sector. Ruminants produce CH4 as a result of fermentation of feed in the rumen especially from roughages which yield more CH4 per unit of biomass ingested as compared to concentrates. Efficient ruminal fermentation is not possible without abating CO2 and CH4. Methane abatement strategies are required to curb the predicted rise in emissions associated with greater ruminant production in future to meet ever increasing animal protein requirements. Ecology of ruminal methanogenesis and avenues for its mitigation can be identified through various genomic and transcriptomic techniques. Programs such as Hungate1000 and the Global Rumen Census have been launched to enhance our understanding about global ruminal microbial communities. Through Hungate1000 project, a comprehensive reference set of rumen microbial genome sequences has been developed from cultivated rumen bacteria and methanogenic archaea along with representative rumen anaerobic fungi and ciliate protozoa cultures. But still many species of rumen microbes are underrepresented especially uncultivable microbes. Lack of sequence information specific to the rumen's microbial community has inhibited efforts to use genomic data to identify specific set of species and their target genes involved in methanogenesis. Metagenomic and metatranscriptomic study of entire microbial rumen populations offer new perspectives to understand interaction of methanogens with other rumen microbes and their potential association with total gas and methane production. Deep understanding of methanogenic pathway will help to devise potentially effective strategies to abate methane production while increasing feed efficiency in ruminants.

Keywords: Genome sequences, Hungate1000, methanogens, ruminal fermentation

Procedia PDF Downloads 121

Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

Procedia PDF Downloads 248

Authors: Ana Vulic, Tina Lesic, Nina Kudumija, Maja Kis, Manuela Zadravec, Nada Vahcic, Tomaz Polak, Jelka Pleadin

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Mycotoxins are toxic secondary metabolites produced by numerous types of molds. They can contaminate both food and feed so that they represent a serious public health concern. Production of dry-fermented meat products involves ripening, during which molds can overgrow the product surface, produce mycotoxins, and consequently contaminate the final product. Citrinin is a mycotoxin produced mainly by the Penicillium citrinum. Data on citrinin occurrence in both food and feed are limited. Therefore, there is a need for research on citrinin occurrence in these types of meat products. The LC-MS/MS method for citrinin determination was developed and validated. Sample preparation was performed using immunoaffinity columns, which resulted in clean sample extracts. Method validation included the determination of the limit of detection (LOD), the limit of quantification (LOQ), recovery, linearity, and matrix effect in accordance to the latest validation guidance. The determined LOD and LOQ were 0.60 µg/kg and 1.98 µg/kg, respectively, showing a good method sensitivity. The method was tested for its linearity in the calibration range of 1 µg/L to 10 µg/L. The recovery was 100.9 %, while the matrix effect was 0.7 %. This method was employed in the analysis of 47 samples of dry-fermented sausages collected from local households. Citrinin wasn’t detected in any of these samples, probably because of the short ripening period of the tested sausages that takes three months tops. The developed method shall be used to test other types of traditional dry-cured products, such as prosciuttos, whose surface is usually more heavily overgrown by surface molds due to the longer ripening period.

Keywords: citrinin, dry-fermented meat products, LC-MS/MS, mycotoxins

Procedia PDF Downloads 105