Search results for: lipid extract

Authors: Nazanin Ahmadi Daryakenari

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Background: Diabetes significantly influences the risk of heart failure. The interplay between distinct types of diabetes, heart failure, and their distribution across various age groups remains an area of active exploration. This study endeavors to scrutinize the age group distribution in publications addressing Type 1 and Type 2 diabetes and heart failure on PubMed while also examining the evolving publication trends. Methods: We leveraged E-utilities and RegEx to search and extract publication data from PubMed using various mesh terms. Subsequently, we conducted descriptive statistics and t-tests to discern the differences between the two diabetes types and the distribution across age groups. Finally, we analyzed the temporal trends of publications concerning both types of diabetes and heart failure. Results: Our findings revealed a divergence in the age group distribution between Type 1 and Type 2 diabetes within heart failure publications. Publications discussing Type 2 diabetes and heart failure were more predominant among older age groups, whereas those addressing Type 1 diabetes and heart failure displayed a more balanced distribution across all age groups. The t-test revealed no significant difference in the means between the two diabetes types. However, the number of publications exploring the relationship between Type 2 diabetes and heart failure has seen a steady increase over time, suggesting an escalating interest in this area. Conclusion: The dissection of publication patterns on PubMed uncovers a pronounced association between Type 2 diabetes and heart failure within older age groups. This highlights the critical need to comprehend the distinct age group differences when examining diabetes and heart failure to inform and refine targeted prevention and treatment strategies.

Keywords: Type 1 diabetes, Type 2 diabetes, heart failure, age groups, publication patterns, PubMed

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Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

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This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

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Authors: Thilivhali Emmanuel Tshikalange, Darky Cheron Modishane, Frederick Tawi Tabit

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The fruit pulp extracts of twelve selected ethnobotanical wild edible fruits from Mutale local municipality in Venda (Limpopo Province, South Africa) were investigated for their antimicrobial, antioxidant and cytotoxicity activities. Methanol extracts were prepared and tested against six micro-organisms (Salmonella typhi, Streptococcus pyogenes, Bacillus cereus, Klebsiella pneumoniae, Prevotella intermedia and Candida albicans). The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were determined using the micro-dilution method, while for antioxidant activity the 2,2-diphenyl-1-picrylhydrazyl method was used. Of the 12 extracts tested, Adonsonia digitata, Berchemia discolor, Manilkara mochisia, Xanthocercis zambesiaca, Landolphia kirkii and Garcinia livingstonei showed antimicrobial activity, with MIC values ranging from 12.5 to 0.4 mg/ml. Gram negative bacteria were more resistant to the extracts in comparison to Gram positive bacteria. Antioxidant activity was only detected in Adonsonia digitata extract and the IC50 (substrate concentration to produce 50% reduction) was found to be 16.18µg/ml. The cytotoxicity of the extracts that showed antimicrobial and antioxidant activities was also determined. All plant extracts tested were non-toxic against human kidney cells (HEK293), with IC50 values of >400 µg/ml. The results presented in this study provide support to some traditional uses of wild edible fruits.

Keywords: antimicrobial, antioxidant, cytotoxicity, ethnobotanical, fruits

Procedia PDF Downloads 392

Authors: K. H. Teng, A. Shaw, M. Ateeq, A. Al-Shamma'a, S. Wylie, S. N. Kazi, B. T. Chew

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Numerical and experimental of using novel electromagnetic wave technique to detect water hardness concentration has been presented in this paper. Simulation is powerful and efficient engineering methods which allow for a quick and accurate prediction of various engineering problems. The RF module is used in this research to predict and design electromagnetic wave propagation and resonance effect of a guided wave to detect water hardness concentration in term of frequency domain, eigenfrequency, and mode analysis. A cylindrical cavity resonator is simulated and designed in the electric field of fundamental mode (TM010). With the finite volume method, the three-dimensional governing equations were discretized. Boundary conditions for the simulation were the cavity materials like aluminum, two ports which include transmitting and receiving port, and assumption of vacuum inside the cavity. The design model was success to simulate a fundamental mode and extract S21 transmission signal within 2.1 – 2.8 GHz regions. The signal spectrum under effect of port selection technique and dielectric properties of different water concentration were studied. It is observed that the linear increment of magnitude in frequency domain when concentration increase. The numerical results were validated closely by the experimentally available data. Hence, conclusion for the available COMSOL simulation package is capable of providing acceptable data for microwave research.

Keywords: electromagnetic wave technique, frequency domain, signal spectrum, water hardness concentration

Procedia PDF Downloads 272

Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Irina M. Kolesnikova, Andrey M. Gaponov, Sergey A. Roumiantsev, Tatiana V. Grigoryeva, Alexander V. Laikov, Alexander V. Shestopalov

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Background. Neuropathy is a common complication of obesity. In this regard, the content of neurotrophins in such patients is of particular interest. Neurotrophins are the proteins that regulate neuron survival and neuroplasticity and include brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF). However, the risk of complications depends on the metabolic type of obesity. Metabolically unhealthy obesity (MUHO) is associated with a high risk of complications, while this is not the case with metabolically healthy obesity (MHO). Therefore, the aim of our work was to study the effect of the obesity metabolic type on serum neurotrophins levels. Patients, materials, methods. The study included 134 healthy donors and 104 obese patients. Depending on the metabolic type of obesity, the obese patients were divided into subgroups with MHO (n=40) and MUHO (n=55). In the blood serum, the concentration of BDNF and NGF was determined. In addition, the content of adipokines (leptin, asprosin, resistin, adiponectin), myokines (irisin, myostatin, osteocrin), indicators of carbohydrate, and lipid metabolism were measured. Correlation analysis revealed the relationship between the studied parameters. Results. We found that serum BDNF concentration was not different between obese patients and healthy donors, regardless of obesity metabolic type. At the same time, in obese patients, there was a decrease in serum NGF level versus control. A similar trend was characteristic of both MHO and MUHO. However, MUHO patients had a higher NGF level than MHO patients. The literature indicates that obesity is associated with an increase in the plasma concentration of NGF. It can be assumed that in obesity, there is a violation of NGF storage in platelets, which accelerates neurotrophin degradation. We found that BDNF concentration correlated with irisin levels in MUHO patients. Healthy donors had a weak association between NGF and VEGF levels. No such association was found in obese patients, but there was an association between NGF and leptin concentrations. In MHO, the concentration of NHF correlated with the content of leptin, irisin, osteocrin, insulin, and the HOMA-IR index. But in MUHO patients, we found only the relationship between NGF and adipokines (leptin, asprosin). It can be assumed that in patients with MHO, the replenishment of serum NGF occurs under the influence of muscle and adipose tissue. In the MUHO patients only the effect of adipose tissue on NGF was observed. Conclusion. Obesity, regardless of metabolic type, is associated with a decrease in serum NGF concentration. We showed that muscle and adipose tissues make a significant contribution to the serum NGF pool in the MHO patients. In MUHO there is no effect of muscle on the NGF level, but the effect of adipose tissue remains.

Keywords: neurotrophins, nerve growth factor, NGF, brain-derived neurotrophic factor, BDNF, obesity, metabolically healthy obesity, metabolically unhealthy obesity

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Authors: Veselin Nanev, Margarita Gabrashanska, Neli Tsocheva-Gaytandzieva

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Ascaridiasis in chicks is one of the major causes for the reduction in body weights, higher mortality, and reduction in egg production, worse meat quantity, pathological lesions, blood losses, and secondary infections. It is responsible for economic losses to the poultry. Despite being economically important parasite, little work has been carried out on the role of antioxidants in the pathogenesis of ascaridiasis. Zinc is a trace elements with multiple functions and one of them is its antioxidant ability. The aim of this study was to investigate the combined effect of organic zinc compound (2Gly.ZnCl22H20) and Ascaridia galli infection on the antioxidant status of broiler chicks. The activity of antioxidant enzymes superoxide dismutase, glutathione peroxidase, the level of lipid peroxidation, expressed by malonyl dialdexyde and plasma zinc in chicks experimentally infected with Ascaridia galli was investigated. Parasite burden was studied as well. The study was performed on 80 broiler chicks, Cobb 500 hybrids. They were divided into four groups – 1st group – control (non-treated and non-infected, 2nd group – infected with embryonated eggs of A. galli and without treatment, 3rd group- only treated with 2Gly.ZnCl22H20 compound and gr. 4 - infected and supplemented with Zn-compound. The chicks in gr. 2 and 4 were infected orally with 450 embryonated eggs of A.galli on day 14 post infection. The chicks from gr. 3 and 4 received 40 mg Zn compound /kg of feed after the 1st week of age during 10 days. All chicks were similarly fed, managed and killed at 60 day p.i. Helminthological, biochemical and statistical methods were applied. Reduced plasma Zn content was observed in the infected chicks compared to controls. Zinc supplementation did not restored the lower Zn content. Cu, Zn-SOD was decreased significantly in the infected chicks compared to controls. The GPx – activity was significantly increased in the infected chicks than the controls. Increased GPx activity together with decreased Cu/ZnSOD activity revealed unbalanced antioxidant defense capacity. The increased MDA level in chicks and changes in the activity of the enzymes showed a development of oxidative stress during the infection with A.galli. Zn compound supplementation has been shown to influence the activity of both antioxidant enzymes (SOD, GPx) and reduced MDA in the infected chicks. Organic zinc supplementation improved the antioxidant defense and protect hosts from oxidant destruction, but without any effect on the parasite burden. The number of helminths was similar in both groups. Zn supplementation did not changed the number of parasites. Administration of oral 2Gly.ZnCl22H20 compound has been shown to be useful in chicks infected with A. galli by its improvement of their antioxidant potential.

Keywords: Ascaridia galli, antioxidants, broiler chicks, zinc supplementation

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Authors: Mohammad A. Bani-Khaled

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In this work we use the Discrete Proper Orthogonal Decomposition transform to characterize the properties of coupled dynamics in thin-walled beams by exploiting numerical simulations obtained from finite element simulations. The outcomes of the will improve our understanding of the linear and nonlinear coupled behavior of thin-walled beams structures. Thin-walled beams have widespread usage in modern engineering application in both large scale structures (aeronautical structures), as well as in nano-structures (nano-tubes). Therefore, detailed knowledge in regard to the properties of coupled vibrations and buckling in these structures are of great interest in the research community. Due to the geometric complexity in the overall structure and in particular in the cross-sections it is necessary to involve computational mechanics to numerically simulate the dynamics. In using numerical computational techniques, it is not necessary to over simplify a model in order to solve the equations of motions. Computational dynamics methods produce databases of controlled resolution in time and space. These numerical databases contain information on the properties of the coupled dynamics. In order to extract the system dynamic properties and strength of coupling among the various fields of the motion, processing techniques are required. Time- Proper Orthogonal Decomposition transform is a powerful tool for processing databases for the dynamics. It will be used to study the coupled dynamics of thin-walled basic structures. These structures are ideal to form a basis for a systematic study of coupled dynamics in structures of complex geometry.

Keywords: coupled dynamics, geometric complexity, proper orthogonal decomposition (POD), thin walled beams

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Authors: Zhifei Hu, Feng Xia

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In recent years, Graph neural network has been widely used in knowledge graph recommendation. The existing recommendation methods based on graph neural network extract information from knowledge graph through entity and relation, which may not be efficient in the way of information extraction. In order to better propose useful entity information for the current recommendation task in the knowledge graph, we propose an end-to-end Neural network Model based on multi-stream graph attentional Mechanism (MSGAT), which can effectively integrate the knowledge graph into the recommendation system by evaluating the importance of entities from both users and items. Specifically, we use the attention mechanism from the user's perspective to distil the domain nodes information of the predicted item in the knowledge graph, to enhance the user's information on items, and generate the feature representation of the predicted item. Due to user history, click items can reflect the user's interest distribution, we propose a multi-stream attention mechanism, based on the user's preference for entities and relationships, and the similarity between items to be predicted and entities, aggregate user history click item's neighborhood entity information in the knowledge graph and generate the user's feature representation. We evaluate our model on three real recommendation datasets: Movielens-1M (ML-1M), LFM-1B 2015 (LFM-1B), and Amazon-Book (AZ-book). Experimental results show that compared with the most advanced models, our proposed model can better capture the entity information in the knowledge graph, which proves the validity and accuracy of the model.

Keywords: graph attention network, knowledge graph, recommendation, information propagation

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Authors: Rajasekhar Reddy Poonuru, Anusha Parnem

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Purpose: To formulate proliposome powder of agomelatine, an antipsychotic drug, and to evaluate physicochemical, in vitro characters and effect of surface charge on ex vivo intestinal permeation. Methods: Film deposition technique was employed to develop proliposomal powders of agomelatin with varying molar ratios of lipid Hydro Soy PC L-α-phosphatidylcholine (HSPC) and cholesterol with fixed sum of drug. With the aim to derive free flowing and stable proliposome powder, fluid retention potential of various carriers was examined. Liposome formation and number of vesicles formed for per mm3 up on hydration, vesicle size, and entrapment efficiency was assessed to deduce an optimized formulation. Sodium cholate added to optimized formulation to induce surface charge on formed vesicles. Solid-state characterization (FTIR, DSC, and XRD) was performed with the intention to assess native crystalline and chemical behavior of drug. The in vitro dissolution test of optimized formulation along with pure drug was evaluated to estimate dissolution efficiency (DE) and relative dissolution rate (RDR). Effective permeability co-efficient (Peff(rat)) in rat and enhancement ratio (ER) of drug from formulation and pure drug dispersion were calculated from ex vivo permeation studies in rat ileum. Results: Proliposomal powder formulated with equimolar ratio of HSPC and cholesterol ensued in higher no. of vesicles (3.95) with 90% drug entrapment up on hydration. Neusilin UFL2 was elected as carrier because of its high fluid retention potential (4.5) and good flow properties. Proliposome powder exhibited augmentation in DE (60.3 ±3.34) and RDR (21.2±01.02) of agomelation over pure drug. Solid state characterization studies demonstrated the transformation of native crystalline form of drug to amorphous and/or molecular state, which was in correlation with results obtained from in vitro dissolution test. The elevated Peff(rat) of 46.5×10-4 cm/sec and ER of 2.65 of drug from charge induced proliposome formulation with respect to pure drug dispersion was assessed from ex vivo intestinal permeation studies executed in ileum of wistar rats. Conclusion: Improved physicochemical characters and ex vivo intestinal permeation of drug from charge induced proliposome powder with Neusilin UFL2 unravels the potentiality of this system in enhancing oral delivery of agomelatin.

Keywords: agomelatin, proliposome, sodium cholate, neusilin

Procedia PDF Downloads 136

Authors: J. K. D. M. P. Madara, R. B. L. Dharmawickreme, Linu John, Ivee Boiss

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Flemingia vestita, commonly known as ‘Sohphlang’ is an important medicinal plant found in the North-Eastern region of India, which is traditionally recognized for its anthelmintic properties. This study was aimed to evaluate the phytochemical constituents and antibacterial activity of the tuber skin extracts of the plant species. Methanol, acetone, and water were used to obtain the solvent extractions of the skin peel extracts. Concentrated extracts of skin peel were tested using previously established qualitative phytochemical assays. The antibacterial efficacy of methanol tuber skin extract was tested against Gram-negative and positive microorganisms, namely, Klebsiella pneumonia, Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, and Mycobacterium tuberculosis strains. Agar well diffusion method was employed to determine the zone of inhibition of the plant extracts. Obtained data were statistically analyzed. Methanol extracts of Flemingia vestita were found to be effective against Bacillus subtilis and Mycobacterium tuberculosis at concentrations of 0.5 mg/ml. The reported zone of inhibition for the two strains was 13.3mm ± 0.57 and 16.3mm ± 4.9, respectively. However Klebsiella pneumoniae, Pseudomonas aeruginosa and Escherichia coli were resistant to the plant extracts with no zone of inhibition. Alkaloids, glycosides, and phenols were found to be present in aqueous, methanol, and acetone extracts of the plant in qualitative phytochemical analysis.

Keywords: flemingia vestita, antibacterial activity, phytochemical screening, well diffusion method

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Authors: Babak Safaei, A. M. Fattahi

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Polymer/carbon nanotube nanocomposites have a wide range of promising applications Due to their enhanced properties. In this work, free vibration analysis of single-walled carbon nanotube-reinforced composite plates is conducted in which carbon nanotubes are embedded in an amorphous polyethylene. The rule of mixture based on various types of plate model namely classical plate theory (CLPT), first-order shear deformation theory (FSDT), and higher-order shear deformation theory (HSDT) was employed to obtain fundamental frequencies of the nanocomposite plates. Generalized differential quadrature (GDQ) method was used to discretize the governing differential equations along with the simply supported and clamped boundary conditions. The material properties of the nanocomposite plates were evaluated using molecular dynamic (MD) simulation corresponding to both short-(10,10) SWCNT and long-(10,10) SWCNT composites. Then the results obtained directly from MD simulations were fitted with those calculated by the rule of mixture to extract appropriate values of carbon nanotube efficiency parameters accounting for the scale-dependent material properties. The selected numerical results are presented to address the influences of nanotube volume fraction and edge supports on the value of fundamental frequency of carbon nanotube-reinforced composite plates corresponding to both long- and short-nanotube composites.

Keywords: nanocomposites, molecular dynamics simulation, free vibration, generalized, differential quadrature (GDQ) method

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

Procedia PDF Downloads 348

Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

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Authors: Neha Parekh, Divya Ladha, Poonam Wadhwani, Nisha Shah

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Nano scaled materials have attracted tremendous interest as corrosion inhibitor due to their high surface area on the metal surfaces. It is well known that the zinc oxide nanoparticles have higher reactivity towards aqueous acidic solution. This work presents a new method to incorporate zinc oxide nanoparticles with white sesame seeds extract (nano-green inhibitor) for corrosion protection of zinc in acidic medium. The morphology of the zinc oxide nanoparticles was investigated by TEM and DLS. The corrosion inhibition efficiency of the green inhibitor and nano-green inhibitor was determined by Gravimetric and electrochemical impedance spectroscopy (EIS) methods. Gravimetric measurements suggested that nano-green inhibitor is more effective than green inhibitor. Furthermore, with the increasing temperature, inhibition efficiency increases for both the inhibitors. In addition, it was established the Temkin adsorption isotherm fits well with the experimental data for both the inhibitors. The effect of temperature and Temkin adsorption isotherm revealed Chemisorption mechanism occurring in the system. The activation energy (Ea) and other thermodynamic parameters for inhibition process were calculated. The data of EIS showed that the charge transfer controls the corrosion process. The surface morphology of zinc metal (specimen) in absence and presence of green inhibitor and nano-green inhibitor were performed using Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM) techniques. The outcomes indicated a formation of a protective layer over zinc metal (specimen).

Keywords: corrosion, green inhibitor, nanoparticles, zinc

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

Procedia PDF Downloads 156

Authors: Chang-Hwan Oh, Young-Jong Lee

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In April, 2015, the Ministry of Food and Drug Safety’s announcement that only 10 of the 207 products that list Cynanchum Wilfordii Radix among their ingredients were confirmed to actually contain “iyeobupiso” the counterfeit version of the “baeksuo” raised a fog to consumers who purchased health/functional foods supposedly containing the herbal medicinal material, “baeksuo” in Korean. Baeksuo is the main ingredient of the product “EstroG-100” that contain Phlomis umbrosa and Angelica gigas too (NaturalEndoTech, S.Korea). The hot water extract of the herbal medicinal materials (HMM) was approved as a product specific Health/Functional Food (HFF) having a helpful function to women reaching menopause by Korea Food & Drug Administration (Ministry of Food & Drug Safety at present). The origin of “baeksuo” is the root of Cynanchum wilfordii Hemsley in Korea (But “iyeobupiso, the root of Cynanchum auriculatum Royle ex Wight is considered as the origin of “baeksuo” in China). In Korea, about 116 HMMs are listed as the food materials in Korea Food Code among the total 187 HMMs could be used for food and medicine purpose simultaneously. But there are some chances of the HMMs (shared use for food and medicine purpose) could be misused by the part and HMMs not permitted for HFF such as the “baeksuo” case. In this study, some of HMMs (shared use for food and medicine purpose) are examined to alleviate the misuse chance of HMMs for HFFs in Korea. For the purpose of this study, the origin, shape, edible parts, efficacy and the side effects of the similar HMMs to be misused for HFF are investigated.

Keywords: herbal medicinal materials, healthy/functional foods, misuse, shared use

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Authors: Zhiyong Li, Hiroshi Katayama

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Since 1990s, e-commerce and internet business have been grown gradually over the word and customers tend to express their demand attributes in terms of specification requirement on parts, component, product structure etc. This paper deals with designing effective decoupling points for build to order systems under e-commerce environment, which can be realized through tradeoff relation analysis between two major criteria, customer order lead time and value of work in progress. These KPIs are critical for successful BTO business, namely time-based service effectiveness on coping with customer requirements for the first issue and cost effective ness with risk aversive operations for the second issue. Approach of this paper consists of investigation of successful business standing for BTO scheme, manufacturing model development of this scheme, quantitative evaluation of proposed models by calculation of two KPI values under various decoupling point distributions and discussion of the results brought by pattern of decoupling point distribution, where some cases provide the pareto optimum performances. To extract the relevant trade-off relation between considered KPIs among 2-dimensional resultant performance, useful logic developed by former research work, i.e. Katayama and Fonseca, is applied. Obtained characteristics are evaluated as effective information for managing BTO manufacturing businesses.

Keywords: build-to-order (BTO), decoupling point, e-commerce, order-to-delivery lead time (ODLT), work in progress (WIP)

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Zhi Zhang, Liling Cao, Seyedbabak Momenzadeh, Lisa Davey

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Reinforced concrete (RC) flat slab-column systems are commonly used in residential or office buildings, as the flat slab provides efficient clearance resulting in more stories at a given height than regular reinforced concrete beam-slab system. Punching shear of slab-column joints is a critical component of two-way reinforced concrete flat slab design. The unbalanced moment at the joint is transferred via slab moment and shear forces. ACI 318 provides an equation to evaluate the punching shear under the design load. It is important to note that the design code considers gravity and environmental load when considering the design load combinations, while it does not consider the effect from differential foundation settlement, which may be a governing load condition for the slab design. This paper describes how prestressed reinforced concrete slab punching shear is evaluated based on ACI 318 provisions and finite element analysis. A prestressed reinforced concrete slab under differential settlements is studied using the finite element modeling methodology. The punching shear check equation is explained. The methodology to extract data for punching shear check from the finite element model is described and correlated with the corresponding code provisions. The study indicates that the finite element analysis results should be carefully reviewed and processed in order to perform accurate punching shear evaluation. Conclusions are made based on the case studies to help engineers understand the punching shear behavior in prestressed and non-prestressed reinforced concrete slabs.

Keywords: differential settlement, finite element model, prestressed reinforced concrete slab, punching shear

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Authors: Lista Andriyati, Nurpudji A Taslim

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The human immunodeficiency virus (HIV) patients have potential nutritional and metabolic problems. HIV is a virus that attacks cells T helper and impairs the function of immune cells. Infected individuals gradually become immunodeficient, results in increased susceptibility to a wide range of infections such as tuberculosis (TB). Malnutrition has destructive effects on the immune system and host defense mechanisms. Effective and proper nutritional therapies are important to improve medical outcomes and quality of life, which is associated with functional improvement. A case of 38-years old man admitted to hospital with loss of consciousness and was diagnosed HIV infection and relapse lung TB with severe malnutrition, fever, oral candidiasis, anemia (6.3 g/dL), severe hypoalbuminemia (1.9 g/dL), severe hypokalemia (2.2 mmol/L), immune depletion (1085 /µL) and elevated liver enzyme (ALT 1198/AST 375 U/L). Nutritional intervention by giving 2300 kcal of energy, protein 2 g/IBW/day, carbohydrate 350 g, fat 104 g through enteral and parenteral nutrition. Supplementations administered are zinc, vitamin A, vitamin B1, vitamin B6, vitamin B12, vitamin C, vitamin D, and snakehead fish extract high content of protein albumin (Pujimin®). After 46 days, there are clinical and metabolic improvement in Hb (6.3 to 11.2 g/dL), potassium (2.2 to 3.4 mmol/L), albumin (1.9 to 2.3 g/dL), ALT 1198 to 47/AST 375 to 68 U/L) and improved awareness. In conclusion, nutritional therapy in HIV infection with adequate macronutrients and micronutrients fulfillment and immunonutrition is very important to avoid cachexia and to improve nutritional status and immune disfunction.

Keywords: HIV, hypoalbuminemia, malnutrition, tuberculosis

Procedia PDF Downloads 129

Authors: Manal M. Hamed, Mosad A. Ghareeb, Abdel-Aleem H. Abdel-Aleem, Amal M. Saad, Mohamed S. Abdel-Aziz, Asmaa H. Hadad

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Natural products derived from medicinal plants provide unlimited opportunities for a new medication leads because of the unmatched accessibility of chemical variation. Six compounds were isolated from the n-butanol extract of Callistemon citrinus (Family Myrtaceae), they were identified as; nepetolide (1), callislignan A (2), 6,8-dimethoxy-4,5-dimethyl-3-methyleneisochroman-1-one (3), 3-methyl-7-O-benzoyl-β-D-glucopyranoside (4), 5, 7, 3', 5'-tetrahydroxy-6, 8-di-C-methyl flavanone (5), and (2R,3R,4S,5S)-2,4-bis(4-hydroxyphenyl)-3,5-dihydroxy-tetrahydropyran (6). The isolated compounds were evaluated as antioxidant and antimicrobial agents. The antioxidant activities of the compounds were determined using DPPH-radical scavenging and total antioxidant capacity (TAC) assays. The results indicated that compound (5) was most active in its capacity to scavenge free radicals in the DPPH assay [SC50 value, 4.65 ± 0.74μg/mL] compared to the standard ascorbic acid and exhibited the highest activity in the TAC assay (610.45 ± 1.67mg AAE/g compound). The pure isolates were tested for their antimicrobial activity against four pathogenic microbial strains including Staphylococcus aureus, Methicillin-resistant Staphylococcus aureus (MRSA), Pseudomonas aeruginosa and Candida albicans. Also, the GC/MS analysis of its leaves essential oil presented nine identified compounds representing 91% of the total oil constituents. The outcomes got from this study give a reasonable justification for the medicinal uses of Callistemon citrinus plant.

Keywords: Callistemon citrinus, flavanone, antioxidant activity, antimicrobial activity, essential oil, Myrtaceae

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Authors: Amadou Fall Dia, Maurras Ulbricht Togbe, Aliou Boly, Zakia Kazi Aoul, Elisabeth Metais

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Existing RDF (Resource Description Framework) Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation, IoT applications, drinking water distribution management, and so on. However, processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient results in terms of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones.

Keywords: centrality measures, RDF graphs summary, RDF graphs stream, SPARQL query

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Authors: Nitin Jadhav, Pradeep R. Vavia

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Poor water soluble drugs are difficult to promote for oral drug delivery as they demonstrate poor and variable bioavailability because of its poor solubility and dissolution in GIT fluid. Nowadays lipid based formulations especially self microemulsifying drug delivery system (SMEDDS) is found as the most effective technique. With all the impressive advantages, the need of high amount of surfactant (50% - 80%) is the major drawback of SMEDDS. High concentration of synthetic surfactant is known for irritation in GIT and also interference with the function of intestinal transporters causes changes in drug absorption. Surfactant may also reduce drug activity and subsequently bioavailability due to the enhanced entrapment of drug in micelles. In chronic treatment these issues are very conspicuous due to the long exposure. In addition the liquid self microemulsifying system also suffers from stability issues. Recently one novel approach of solid stabilized micro and nano emulsion (Pickering emulsion) has very admirable properties such as high stability, absence or very less concentration of surfactant and easily converts into the dry form. So here we are exploring pickering dry emulsion system for dissolution enhancement of anti-lipemic, extremely poorly water soluble drug (Fenofibrate). Oil moiety for emulsion preparation was selected mainly on the basis of higher solubility of drug. Captex 300 was showed higher solubility for fenofibrate, hence selected as oil for emulsion. With Silica (solid stabilizer); Span 20 was selected to improve the wetting property of it. Emulsion formed by Silica and Span20 as stabilizer at the ratio 2.5:1 (silica: span 20) was found very stable at the particle size 410 nm. The prepared emulsion was further preceded for spray drying and formed microcapsule evaluated for in-vitro dissolution study, in-vivo pharmacodynamic study and characterized for DSC, XRD, FTIR, SEM, optical microscopy etc. The in vitro study exhibits significant dissolution enhancement of formulation (85 % in 45 minutes) as compared to plain drug (14 % in 45 minutes). In-vivo study (Triton based hyperlipidaemia model) exhibits significant reduction in triglyceride and cholesterol with formulation as compared to plain drug indicating increasing in fenofibrate bioavailability. DSC and XRD study exhibit loss of crystallinity of drug in microcapsule form. FTIR study exhibit chemical stability of fenofibrate. SEM and optical microscopy study exhibit spherical structure of globule coated with solid particles.

Keywords: captex 300, fenofibrate, pickering dry emulsion, silica, span20, stability, surfactant

Procedia PDF Downloads 498

Authors: Somit Dutta, Pallab Kar, Arnab Kumar Chakraborty, Arnab Sen, Tapas Kumar Chaudhuri

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In the present study three species of Clerodendrum; Clerodendrum indicum, Volkameria inermis and Clerodendrum colebrookianum were used to investigate the possible activity against oxidative stress. A detailed in-vivo and in-vitro antioxidant profiling, directly associated with inflammation-related carcinogenesis, has been executed with a motive to evaluate the free radical scavenging activity of Clerodendrum extract. Measurement of cell viability and ROS generation in HEK-293 (Human Embryonic Kidney Cell Line) cells was also estimated. The immune cell proliferative properties (MTT) and in-vitro assay for evaluation of their antioxidant activities including hydroxyl radical, nitric oxide, singlet oxygen, peroxinitrate and hydrogen peroxide, etc. were investigated. GC-MS and FTIR analyses have been performed to identify the active biological compounds. These active biological compounds were further studied to assess their potential medicinal properties, aided by molecular docking and interaction analysis between the active compounds and different proteins related to oxidative stress leading to progression of carcinogenesis. The research article clearly demonstrates the role of ROS in various phases of carcinogenesis. Therefore, the antioxidant and free radical scavenging capacity of all the Clerodendrum species might prove beneficial for the immune system. It might be concluded that this plant species offers great promise for cancer prevention and therapy due to the presence of several bioactive compounds and potent antioxidant capacity of C. colebrookianum.

Keywords: antioxidant, cancer, oxidative stress, reactive oxygen species (ROS)

Procedia PDF Downloads 278

Authors: Theresa Campbell, Camille Bowen-Forbes, William Aalbersberg

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Differences in the sensory properties of two subtly distinct varieties of Rubus rosifolius lead to the examination of their anthocyanin, essential oil and polyphenol profiles. In both cases, notable differences were identified. Pelargonidin-3-rhutinoside (17.2 mg/100 g FW) and Cyanidin-3-glucoside (66.2 mg/100g FW) proved to be the dominant anthocyanins in the red and wine red varieties respectively. Linalool and terpineol were the major constituents of the essential oil from the red variety; however, those of the wine red variety are unidentified. In regard to phenolic compounds, caffeic acid and quercetin were in a higher concentration in the red variety (1.85 and 0.73 mg/100g FW respectively, compared to 1.22 and 0.34 mg/100g FW respectively in the wine red fruits); while ellagic acid and ferulic acid were of a higher concentration in the wine red variety (0.92 and 0.84mg/100g FW respectively, compared to 0.15 and 0.48 mg/100g FW respectively in the red variety). The methanol extract of both fruit varieties showed great antioxidant activity. Analysis of the antimicrobial activity of the fruit extracts against the growth of drug resistant pathogens revealed that they are active against methicillin resistant S. aureus (MRSA), rifampicin resistant S. aureus (RRSA), wild-type S. aureus (WTSA) and vancomycin-resistant Enterococcus faecium (VREF). Activity was also reported against several food-borne pathogens including two strains of E. coli, L. monocytogenes and Enterobacter aerogenes. The cytotoxicity of the various extracts was assessed and the essential oil extracts exhibited superior activity. The phenolic composition and biological activity of the fruits indicate that their consumption is beneficial to health and also that their incorporation into functional foods and nutraceuticals should be considered.

Keywords: phytochemicals, antimicrobial, cytotoxic, Rubus rosifolius

Procedia PDF Downloads 396

Authors: K. Khaerunnisa, D. Ryangga, S. A. Pawiro

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Over the past few decades, film dosimetry has become a tool which is used in various radiotherapy modalities, either for clinical quality assurance (QA) or dose verification. The response of the film to irradiation is usually expressed in optical density (OD) or net optical density (netOD). While the film's response to radiation is not linear, then the use of film as a dosimeter must go through a calibration process. This study aimed to compare the function of the calibration curve of various measurement methods with various densitometer, using a flat bad scanner, point densitometer and spectrophotometer. For every response function, a radichromic film calibration curve is generated from each method by performing accuracy, precision and sensitivity analysis. netOD is obtained by measuring changes in the optical density (OD) of the film before irradiation and after irradiation when using a film scanner if it uses ImageJ to extract the pixel value of the film on the red channel of three channels (RGB), calculate the change in OD before and after irradiation when using a point densitometer, and calculate changes in absorbance before and after irradiation when using a spectrophotometer. the results showed that the three calibration methods gave readings with a netOD precision of doses below 3% for the uncertainty value of 1σ (one sigma). while the sensitivity of all three methods has the same trend in responding to film readings against radiation, it has a different magnitude of sensitivity. while the accuracy of the three methods provides readings below 3% for doses above 100 cGy and 200 cGy, but for doses below 100 cGy found above 3% when using point densitometers and spectrophotometers. when all three methods are used for clinical implementation, the results of the study show accuracy and precision below 2% for the use of scanners and spectrophotometers and above 3% for precision and accuracy when using point densitometers.

Keywords: Callibration Methods, Film Dosimetry EBT3, Flat Bad Scanner, Densitomete, Spectrophotometer

Procedia PDF Downloads 135

Authors: Lee Seungheon, Kim Ba-Ro

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In this study, the anti-stress effects of the ethanolic extract of Hydrangeae Dulcis Folium (EHDF) were investigated. To determine the effects of EHDF on physical stress, changes in the whole-body cortisol level and behaviour were monitored in zebrafish. To induce physical stress, we used the net handling stress (NHS). Fish were treated with EHDF for 6 min before they were exposed to stress, and the fish were either evaluated via behavioural tests, including a novel tank test and an open field test or sacrificed to collect body fluid from the whole body. The results indicate that increased anxiety-like behaviours in the novel tank test and open field test under stress were recovered by treatment with EHDF at 5, 10 and 20 mg/L (P < 0.05). Moreover, compared with the normal group, which was not treated with NHS, the whole-body cortisol level was significantly increased by treatment with NHS in the control group. Compared with the control group, pre-treatment with EHDF at concentrations of 5, 10 and 20 mg/L for 6 min significantly prevented the increase in the whole-body cortisol level induced by NHS (P < 0.05). In addition, adrenocorticotropin hormone (ACTH) challenge studies showed that EHDF completely blocked the effects of ACTH (0.2 IU/g, IP) on cortisol secretion. These results suggest that EHDF may be a good anti-stress candidate and that its mechanism of action may be related to its positive effects on cortisol release.

Keywords: net handling stress, zebrafish, hydrangeae dulcis folium, whole-body cortisol, novel tank test, open field test

Procedia PDF Downloads 299

Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

Procedia PDF Downloads 425