Search results for: time-frequency feature extraction

Authors: Xing Wang, Lin Feng, Xuan Zou, Hongchen liu

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Immediate Implantation after tooth extraction is considered to be the ideal way to retain the alveolar bone, but some scholars believe the aesthetic effect in the Early Implantation case are more reliable. In this study, 89 patients were added to this retrospective study up to 5 years. Assessment indicators was including the survival of the implant (peri-implant infection, implant loosening, shedding, crowns and occlusal), aesthetics (color and fullness gums, papilla height, probing depth, X-ray alveolar crest height, the patient's own aesthetic satisfaction, doctors aesthetics score), repair defects around the implant (peri-implant bone changes in height and thickness, whether the use of autologous bone graft, whether to use absorption/repair manual nonabsorbable material), treatment time, cost and the use of antibiotics.The results demonstrated that there is no significant difference in long-term success rate of immediate implantation, early implantation and delayed implantation (p> 0.05). But the results indicated immediate implantation group could get get better aesthetic results after two years (p< 0.05), but may increase the risk of complications and failures (p< 0.05). High-risk indicators include gingival recession, labial bone wall damage, thin gingival biotypes, planting position and occlusal restoration bad and so on. No matter which type of implanting methods was selected, the extraction methods and bone defect amplification techniques are observed as a significant factors on aesthetic effect (p< 0.05).

Keywords: immediate implantation, long-term effects, aesthetics area, dental implants

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Authors: Kriyapa lairungruang, Arunporn Itharat

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Limonia acidissima L. (LA) (Common name: wood apple, Thai name: ma-khwit) is a medicinal plant which has long been used in Thai traditional medicine. Its bark is used for treatment of diarrhea, abscess, wound healing and inflammation and it is also used in oral cancer. Thus, this research aimed to investigate antioxidant and cytotoxic activities of the LA bark extracts produced by various extraction methods. Different extraction procedures were used to extract LA bark for biological activity testing: boiling in water, maceration with 95% ethanol, maceration with 50% ethanol and water boiling of each the 95% and the 50% ethanolic residues. All extracts were tested for antioxidant activity using DPPH radical scavenging assay, cytotoxic activity against human laryngeal epidermoid carcinoma (HEp-2) cells and human oral epidermoid carcinoma (KB) cells using sulforhodamine B (SRB) assay. The results found that the 95% ethanolic extract of LA bark showed the highest antioxidant activity with EC50 values of 29.76±1.88 µg/ml. For cytotoxic activity, the 50% ethanolic extract showed the best cytotoxic activity against HEp-2 and KB cells with IC50 values of 9.55±1.68 and 18.90±0.86 µg/ml, respectively. This study demonstrated that the 95% ethanolic extract of LA bark showed moderate antioxidant activity and the 50% ethanolic extract provided potent cytotoxic activity against HEp-2 and KB cells. These results confirm the traditional use of LA for the treatment of oral cancer and laryngeal cancer, and also support its ongoing use.

Keywords: antioxidant activity, cytotoxic activity, Laryngeal epidermoid carcinoma, Limonia acidissima L., oral epidermoid carcinoma

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Authors: Ali A. Ukasha, Majdi F. Elbireki, Mohammad F. Abdullah

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Data security needed in data transmission, storage, and communication to ensure the security. This paper is divided into two parts. This work interests with the color image which is decomposed into red, green and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using the key image that has same original size and are generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours from color images recovery can be obtained with accepted level of distortion using single step parallel contour extraction (SSPCE) method. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Color images and completely reconstructed without any distortion. Also shown that the analyzed algorithm has extremely large security against some attacks like salt and pepper and Jpeg compression. Its proof that the color images can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression and salt and peppers attacks, bitplanes decomposition, Arnold transform, color image, wavelet transform, lossless image encryption

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Authors: A: Annis Fathima, V. Vaidehi, S. Ajitha

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Face recognition system finds many applications in surveillance and human computer interaction systems. As the applications using face recognition systems are of much importance and demand more accuracy, more robustness in the face recognition system is expected with less computation time. In this paper, a hybrid approach for face recognition combining Gabor Wavelet and Linear Discriminant Analysis (HGWLDA) is proposed. The normalized input grayscale image is approximated and reduced in dimension to lower the processing overhead for Gabor filters. This image is convolved with bank of Gabor filters with varying scales and orientations. LDA, a subspace analysis techniques are used to reduce the intra-class space and maximize the inter-class space. The techniques used are 2-dimensional Linear Discriminant Analysis (2D-LDA), 2-dimensional bidirectional LDA ((2D)2LDA), Weighted 2-dimensional bidirectional Linear Discriminant Analysis (Wt (2D)2 LDA). LDA reduces the feature dimension by extracting the features with greater variance. k-Nearest Neighbour (k-NN) classifier is used to classify and recognize the test image by comparing its feature with each of the training set features. The HGWLDA approach is robust against illumination conditions as the Gabor features are illumination invariant. This approach also aims at a better recognition rate using less number of features for varying expressions. The performance of the proposed HGWLDA approaches is evaluated using AT&T database, MIT-India face database and faces94 database. It is found that the proposed HGWLDA approach provides better results than the existing Gabor approach.

Keywords: face recognition, Gabor wavelet, LDA, k-NN classifier

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Authors: Aisultan Shoiynbek, Darkhan Kuanyshbay, Paulo Menezes, Akbayan Bekarystankyzy, Assylbek Mukhametzhanov, Temirlan Shoiynbek

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Speech emotion recognition (SER) has received increasing research interest in recent years. It is a common practice to utilize emotional speech collected under controlled conditions recorded by actors imitating and artificially producing emotions in front of a microphone. There are four issues related to that approach: emotions are not natural, meaning that machines are learning to recognize fake emotions; emotions are very limited in quantity and poor in variety of speaking; there is some language dependency in SER; consequently, each time researchers want to start work with SER, they need to find a good emotional database in their language. This paper proposes an approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describes the sequence of actions involved in the proposed approach. One of the first objectives in the sequence of actions is the speech detection issue. The paper provides a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To investigate the working capacity of the developed model, an analysis of speech detection and extraction from real tasks has been performed.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: K. S. Rao, Ankesh Kumar

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The search for alternative energy sources to petroleum has increased these days because of increase in need and depletion of petroleum reserves. Therefore the importance of oil shales as an economically viable substitute has increased many folds in last 20 years. The technologies like hydro-fracturing have opened the field of oil extraction from these unconventional rocks. Oil shale is a compact laminated rock of sedimentary origin containing organic matter known as kerogen which yields oil when distilled. Oil shales are formed from the contemporaneous deposition of fine grained mineral debris and organic degradation products derived from the breakdown of biota. Conditions required for the formation of oil shales include abundant organic productivity, early development of anaerobic conditions, and a lack of destructive organisms. These rocks are not gown through the high temperature and high pressure conditions in Mother Nature. The most common approach for oil extraction is drastically breaking the bond of the organics which involves retorting process. The two approaches for retorting are surface retorting and in-situ processing. The most environmental friendly approach for extraction is In-situ processing. The three steps involved in this process are fracturing, injection to achieve communication, and fluid migration at the underground location. Upon heating (retorting) oil shale at temperatures in the range of 300 to 400°C, the kerogen decomposes into oil, gas and residual carbon in a process referred to as pyrolysis. Therefore it is very important to understand the physico-mechenical behavior of such rocks, to improve the technology for in-situ extraction. It is clear from the past research and the physical observations that these rocks will behave as an anisotropic rock so it is very important to understand the mechanical behavior under high pressure at different orientation angles for the economical use of these resources. By knowing the engineering behavior under above conditions will allow us to simulate the deep ground retorting conditions numerically and experimentally. Many researchers have investigate the effect of organic content on the engineering behavior of oil shale but the coupled effect of organic and inorganic matrix is yet to be analyzed. The favourable characteristics of Assam coal for conversion to liquid fuels have been known for a long time. Studies have indicated that these coals and carbonaceous shale constitute the principal source rocks that have generated the hydrocarbons produced from the region. Rock cores of the representative samples are collected by performing on site drilling, as coring in laboratory is very difficult due to its highly anisotropic nature. Different tests are performed to understand the petrology of these samples, further the chemical analyses are also done to exactly quantify the organic content in these rocks. The mechanical properties of these rocks are investigated by considering different anisotropic angles. Now the results obtained from petrology and chemical analysis are correlated with the mechanical properties. These properties and correlations will further help in increasing the producibility of these rocks. It is well established that the organic content is negatively correlated to tensile strength, compressive strength and modulus of elasticity.

Keywords: oil shale, producibility, hydro-fracturing, kerogen, petrology, mechanical behavior

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Authors: Sharareh Mohseni

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Purpose: The objective of this study was to find a suitable solvent to produce saffron edible extract with improved chemical properties. Design/methodology/approach: Dried and pulverized stigmas of C. sativus L. (10g) was extracted with 300 ml of solvents including: distillated water (DW), ethanol/DW, methanol/DW, propylene glycol/DW, heptan/DW, and hexan/DW, for 3 days at 25°C and then centrifuged at 3000 rpm. Then the extracts were evaporated using rotary evaporator at 40°C. The fiber and solvent-free extracts were then analyzed by UV spectrophotometer to detect saffron quality parameters including crocin, picrocrocin and safranal. Findings: Distilled water/ethanol mixture as the extraction solvent, caused larger amounts of the plant constituents to diffuse out to the extract compared to other treatments and also control. Polar solvents including distilled water, ethanol, and propylene glycol (except methanol) were more effective in extracting crocin, picrocrocin, and saffranal than non-polar solvents. Social implications: Due to an enhancement of color and flavor, saffron extract is economical compared to natural saffron. Saffron Extract saves on preparation time and reduces the amount of saffron required for imparting the same flavor, as compared to dry saffron. Liquid extract is easier to use and standardize in food preparations compared to dry stamens and can be dosed precisely compared to natural saffron. Originality/value: No research had been done on production of saffron edible extract using the solvent studied in this survey. The novelty of this research is high and the results can be used industrially.

Keywords: Crocus sativus L., saffron extract, solvent extraction, distilled water

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

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Authors: Serpa A. M., Gómez Hoyos C., Velásquez-Cock J. A., Ruiz L. F., Vélez Acosta L. M., Gañan P., Zuluaga R.

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Turmeric (Curcuma Longa L) is an Indian rhizome known for its biological properties, derived from its active compounds such as curcuminoids. Curcumin, the main polyphenol in turmeric, only represents around 3.5% of the dehydrated rhizome and extraction yields between 41 and 90% have been reported. Therefore, for every 1000 tons of turmeric powder used for the extraction of curcumin, around 970 tons of residues are generated. The present study evaluates the effect of different mechanical treatments (waring blender, grinder and high-pressure homogenization) on the physical and chemical properties of turmeric, as an alternative for the transformation of the entire rhizome. Suspensions of turmeric (10, 20 y 30%) were processed by waring blender during 3 min at 12000 rpm, while the samples treated by grinder were processed evaluating two different Gaps (-1 and -1,5). Finally, the process by high-pressure homogenization, was carried out at 500 bar. According to the results, the luminosity of the samples increases with the severity of the mechanical treatment, due to the stabilization of the color associated with the inactivation of the oxidative enzymes. Additionally, according to the microstructure of the samples, the process by grinder (Gap -1,5) and by high-pressure homogenization allowed the largest size reduction, reaching sizes up to 3 m (measured by optical microscopy). This processes disrupts the cells and breaks their fragments into small suspended particles. The infrared spectra obtained from the samples using an attenuated total reflectance accessory indicates changes in the 800-1200 cm⁻¹ region, related mainly to changes in the starch structure. Finally, the thermogravimetric analysis shows the presence of starch, curcumin and some minerals in the suspensions.

Keywords: characterization, mechanical treatments, suspensions, turmeric rhizome

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Authors: Nataša Stojić, Mira Pucarević, Nebojša Ralević, Vojislava Bursić, Gordan Stojić

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Surface soil (0 – 10 cm) samples from 52 sampling sites along the length of railway tracks on the territory of Srem (the western part of the Autonomous Province of Vojvodina, itself part of Serbia) were collected and analyzed for 7 polychlorinated biphenyls (PCBs) in order to see how the distance from the railroad on the one hand and dump on the other hand, affect the concentration of PCBs (CPCBs) in the soil. Samples were taken at a distance of 0.03 to 4.19 km from the railway and 0.43 to 3.35 km from the landfills. For the soil extraction the Soxhlet extraction (USEPA 3540S) was used. The extracts were purified on a silica-gel column (USEPA 3630C). The analysis of the extracts was performed by gas chromatography with tandem mass spectrometry. PCBs were not detected only at two locations. Mean total concentration of PCBs for all other sampling locations was 0,0043 ppm dry weight (dw) with a range of 0,0005 to 0,0227 ppm dw. On the part of the data that were interesting for this research with statistical methods (PCA) were isolated factors that affect the concentration of PCBs. Data were also analyzed using the Pearson's chi-squared test which showed that the hypothesis of independence of CPCBs and distance from the railway can be rejected. Hypothesis of independence between CPCB and the percentage of humus in the soil can also be rejected, in contrast to dependence of CPCB and the distance from the landfill where the hypothesis of independence cannot be rejected. Based on these results can be said that railway transport is a potential source of PCBs. The next step in this research is to establish the position of transformers which are located near sampling sites as another important factor that affects the concentration of PCBs in the soil.

Keywords: GC/MS, landfill, PCB, railway, soil

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Authors: Mohsen Maraoui

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In the aim of natural language processing applications improvement, such as information retrieval, machine translation, lexical disambiguation, we focus on statistical approach to semantic indexing for multilingual text documents based on conceptual network formalism. We propose to use this formalism as an indexing language to represent the descriptive concepts and their weighting. These concepts represent the content of the document. Our contribution is based on two steps. In the first step, we propose the extraction of index terms using the multilingual lexical resource Euro WordNet (EWN). In the second step, we pass from the representation of index terms to the representation of index concepts through conceptual network formalism. This network is generated using the EWN resource and pass by a classification step based on association rules model (in attempt to discover the non-taxonomic relations or contextual relations between the concepts of a document). These relations are latent relations buried in the text and carried by the semantic context of the co-occurrence of concepts in the document. Our proposed indexing approach can be applied to text documents in various languages because it is based on a linguistic method adapted to the language through a multilingual thesaurus. Next, we apply the same statistical process regardless of the language in order to extract the significant concepts and their associated weights. We prove that the proposed indexing approach provides encouraging results.

Keywords: concept extraction, conceptual network formalism, fuzzy association rules, multilingual thesaurus, semantic indexing

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Authors: Soomal Hamza, Uzma Imran

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Organochlorine pesticides bio-accumulate into the fat of fish, birds, and animals through which it enters the human food cycle. Due to their persistence and stability in the environment, many health impacts are associated with them, most of which are carcinogenic in nature. In this study, the level of organochlorine pesticides has been detected in Keenjhar Lake and remediated using Rhizoremediation technique. 14 OC pesticides namely, Aldrin, Deldrin, Heptachlor, Heptachlor epoxide, Endrin, Endosulfun I and II, DDT, DDE, DDD, Alpha, Beta, Gamma BHC and two plants namely, Water Hyacinth and Slvinia Molesta were used in the system using pot experiment which processed for 11 days. A consortium was inoculated in both plants to increase its efficiency. Water samples were processed using liquide-liquid extraction. Sediments and roots samples were processed using Soxhlet method followed by clean-up and Gas Chromatography. Delta-BHC was the predominantly found in all samples with mean concentration (ppb) and standard deviation of 0.02 ± 0.14, 0.52 ± 0.68, 0.61 ± 0.06, in Water, Sediments and Roots samples respectively. The highest levels were of Endosulfan II in the samples of water, sediments and roots. Water Hyacinth proved to be better bioaccumulaor as compared to Silvinia Molesta. The pattern of compounds reduction rate by the end of experiment was Delta-BHC>DDD > Alpha-BHC > DDT> Heptachlor> H.Epoxide> Deldrin> Aldrin> Endrin> DDE> Endosulfun I > Endosulfun II. Not much significant difference was observed between the pots with the consortium and pots without the consortium addition. Phytoremediation is a promising technique, but more studies are required to assess the bioremediation potential of different aquatic plants and plant-endophyte relationship.

Keywords: aquatic plant, bio remediation, gas chromatography, liquid liquid extraction

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Authors: Jaruwan Duangchuen, Siwalak Pathaveerat

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Coconut (Cocos nucifera) belongs to the family Arecaceae. Coconut juice and meat are consumed as food and dessert in several regions of the world. Coconut juice contains low proteins, and arginine is the main amino acid content. Coconut meat is the endosperm of coconut that has nutritional value. It composes of carbohydrate, protein and fat. The objective of this study is utilization of by-products from the virgin coconut oil extraction process by using the skimmed coconut milk as a powder. The skimmed coconut milk was separated from the coconut milk in virgin coconut oil extraction process that consists approximately of protein 6.4%, carbohydrate 7.2%, dietary fiber 0.27 %, sugar 6.27%, fat 3.6 % and moisture content of 86.93%. This skimmed coconut milk can be made to powder for value - added product by using spray drying. The factors effect to the yield and properties of dry skimmed coconut milk in spraying process are inlet, outlet air temperature and the maltodextrin concentration. The percentage of maltodextrin content (15, 20%), outlet air temperature (80 ºC, 85 ºC, 90 ºC) and inlet air temperature (190 ºC, 200 ºC, 210 ºC) were conducted to the skimmed coconut milk spray drying process. The spray dryer was kept air flow rate (0.2698 m3 /s). The result that shown 2.22 -3.23% of moisture content, solubility, bulk density (0.4-0.67g/mL), solubility, wettability (4.04 -19.25 min) for solubility in the water, color, particle size were analyzed for the powder samples. The maximum yield (18.00%) of spray dried coconut milk powder was obtained at 210 °C of temperature, 80°C of outlet temperature and 20% maltodextrin for 27.27 second for drying time. For the amino analysis shown that the high amino acids are Glutamine (16.28%), Arginine (10.32%) and Glycerin (9.59%) by using HPLP method (UV detector).

Keywords: skimmed coconut milk, spray drying, virgin coconut oil process (VCO), maltodextrin

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Authors: N. Prabavathy, R. Balasundaraprabhu, S. Shalini, Dhayalan Velauthapillai, S. Prasanna, N. Muthukumarasamy

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Dye sensitized solar cell (DSSC) has become a significant research area due to their fundamental and scientific importance in the area of energy conversion. Synthetic dyes as sensitizer in DSSC are efficient and durable but they are costlier, toxic and have the tendency to degrade. Natural sensitizers contain plant pigments such as anthocyanin, carotenoid, flavonoid, and chlorophyll which promote light absorption as well as injection of charges to the conduction band of TiO2 through the sensitizer. But, the efficiency of natural dyes is not up to the mark mainly due to instability of the pigment such as anthocyanin. The stability issues in vitro are mainly due to the effect of solvents on extraction of anthocyanins and their respective pH. Taking this factor into consideration, in the present work, the anthocyanins were extracted from the flower Caesalpinia pulcherrima (C. pulcherrimma) with various solvents and their respective stability and pH values are discussed. The usage of citric acid as solvent to extract anthocyanin has shown good stability than other solvents. It also helps in enhancing the sensitization properties of anthocyanins with Titanium dioxide (TiO2) nanorods. The IPCE spectra show higher photovoltaic performance for dye sensitized TiO2nanorods using citric acid as solvent. The natural DSSC using citric acid as solvent shows a higher efficiency compared to other solvents. Hence citric acid performs to be a safe solvent for natural DSSC in boosting the photovoltaic performance and maintaining the stability of anthocyanins.

Keywords: Caesalpinia pulcherrima, citric acid, dye sensitized solar cells, TiO₂ nanorods

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Authors: Zarina Chokparova, Ighor Uzhinsky

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Carbon dioxide emissions resulting from burning of the fossil fuels on large scales, such as oil industry or power plants, leads to a plenty of severe implications including global temperature raise, air pollution and other adverse impacts on the environment. Besides some precarious and costly ways for the alleviation of CO₂ emissions detriment in industrial scales (such as liquefaction of CO₂ and its deep-water treatment, application of adsorbents and membranes, which require careful consideration of drawback effects and their mitigation), one physically and commercially available technology for its capture and disposal is supersonic system for inertial extraction of CO₂ in after-combustion streams. Due to the flue gas with a carbon dioxide concentration of 10-15 volume percent being emitted from the combustion system, the waste stream represents a rather diluted condition at low pressure. The supersonic system induces a flue gas mixture stream to expand using a converge-and-diverge operating nozzle; the flow velocity increases to the supersonic ranges resulting in rapid drop of temperature and pressure. Thus, conversion of potential energy into the kinetic power causes a desublimation of CO₂. Solidified carbon dioxide can be sent to the separate vessel for further disposal. The major advantages of the current solution are its economic efficiency, physical stability, and compactness of the system, as well as needlessness of addition any chemical media. However, there are several challenges yet to be regarded to optimize the system: the way for increasing the size of separated CO₂ particles (as they are represented on a micrometers scale of effective diameter), reduction of the concomitant gas separated together with carbon dioxide and provision of CO₂ downstream flow purity. Moreover, determination of thermodynamic conditions of the vapor-solid mixture including specification of the valid and accurate equation of state remains to be an essential goal. Due to high speeds and temperatures reached during the process, the influence of the emitted heat should be considered, and the applicable solution model for the compressible flow need to be determined. In this report, a brief overview of the current technology status will be presented and a program for further evaluation of this approach is going to be proposed.

Keywords: CO₂ sequestration, converging diverging nozzle, fossil fuel power plant emissions, inertial CO₂ extraction, supersonic post-combustion carbon dioxide capture

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Authors: Ali Hamza

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Accurate segmentation of breast ultrasound images is of paramount importance in enhancing the diagnostic capabilities of breast cancer detection. This study presents an approach utilizing the U-Net architecture for segmenting breast ultrasound images aimed at improving the accuracy and reliability of mass identification within the breast tissue. The proposed method encompasses a multi-stage process. Initially, preprocessing techniques are employed to refine image quality and diminish noise interference. Subsequently, the U-Net architecture, a deep learning convolutional neural network (CNN), is employed for pixel-wise segmentation of regions of interest corresponding to potential breast masses. The U-Net's distinctive architecture, characterized by a contracting and expansive pathway, enables accurate boundary delineation and detailed feature extraction. To evaluate the effectiveness of the proposed approach, an extensive dataset of breast ultrasound images is employed, encompassing diverse cases. Quantitative performance metrics such as the Dice coefficient, Jaccard index, sensitivity, specificity, and Hausdorff distance are employed to comprehensively assess the segmentation accuracy. Comparative analyses against traditional segmentation methods showcase the superiority of the U-Net architecture in capturing intricate details and accurately segmenting breast masses. The outcomes of this study emphasize the potential of the U-Net-based segmentation approach in bolstering breast ultrasound image analysis. The method's ability to reliably pinpoint mass boundaries holds promise for aiding radiologists in precise diagnosis and treatment planning. However, further validation and integration within clinical workflows are necessary to ascertain their practical clinical utility and facilitate seamless adoption by healthcare professionals. In conclusion, leveraging the U-Net architecture for breast ultrasound image segmentation showcases a robust framework that can significantly enhance diagnostic accuracy and advance the field of breast cancer detection. This approach represents a pivotal step towards empowering medical professionals with a more potent tool for early and accurate breast cancer diagnosis.

Keywords: mage segmentation, U-Net, deep learning, breast cancer detection, diagnostic accuracy, mass identification, convolutional neural network

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Authors: M. Goliszek, M. Sobiesiak, O. Sevastyanova, B. Podkoscielna

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Lignin is one of three main constituents of biomass together with cellulose and hemicellulose. It is a complex biopolymer, which contains a large number of functional groups, including aliphatic and aromatic hydroxyl groups, carbohylic groups and methoxy groups in its structure, that is why it shows potential capacities for process of sorption. Lignin is a highly cross-linked polymer with a three-dimentional structure which can provide large surface area and pore volumes. It can also posses better dispersion, diffusion and mass transfer behavior in a field of the removal of, e.g., heavy-metal-ions or aromatic pollutions. In this work emulsion-suspension copolymerization method, to synthesize the porous microspheres of divinylbenzene (DVB), styrene (St) and lignin was used. There are also microspheres without the addition of lignin for comparison. Before the copolymerization, modification lignin with methacryloyl chloride, to improve its reactivity with other monomers was done. The physico-chemical properties of the obtained microspheres, e.g., pore structures (adsorption-desorption measurements), thermal properties (DSC), tendencies to swell and the actual shapes were also studied. Due to well-developed porous structure and the presence of functional groups our materials may have great potential in sorption processes. To estimate the sorption capabilities of the microspheres towards phenol and its chlorinated derivatives the off-line SPE (solid-phase extraction) method is going to be applied. This method has various advantages, including low-cost, easy to use and enables the rapid measurements for a large number of chemicals. The efficiency of the materials in removing phenols from aqueous solution and in desorption processes will be evaluated.

Keywords: microspheres, lignin, sorption, solid-phase extraction

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Authors: Igor P. Maximkin, Arkady A. Yukhimchuk, Victor V. Baluev, Igor L. Malkov, Rafael K. Musyaev, Damir T. Sitdikov, Alexey V. Buchirin, Vasily V. Tikhonov

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Minimization of tritium diffusion leakage when developing devices handling tritium-containing media is key problems whose solution will at least allow essential enhancement of radiation safety and minimization of diffusion losses of expensive tritium. One of the ways to solve this problem is to use Al₂O₃ high-strength non-porous ceramics as a structural material of the bed body. This alumina ceramics offers high strength characteristics, but its main advantages are low hydrogen permeability (as against the used structural material) and high dielectric properties. The latter enables direct induction heating of an hydride-forming metal without essential heating of the pressure and containment vessel. The use of alumina ceramics and induction heating allows: - essential reduction of tritium extraction time; - several orders reduction of tritium diffusion leakage; - more complete extraction of tritium from metal hydrides due to its higher heating up to melting in the event of final disposal of the device. The paper presents computational and experimental results for the tritium bed designed to absorb 6 liters of tritium. Titanium was used as hydrogen isotope sorbent. Results of hydrogen realize kinetic from hydride-forming metal, strength and cyclic service life tests are reported. Recommendations are also provided for the practical use of the given bed type.

Keywords: aluminum oxide ceramic, hydrogen pressure, hydrogen isotope storage, titanium hydride

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Authors: F. Deng, R. Sanchez, A. Beltran, S. Maestre

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The high nutritional value associated with seafood is related to the presence of essential trace elements. Moreover, seafood is considered an important source of energy, proteins, and long-chain polyunsaturated fatty acids. Generally, seafood is consumed cooked. Consequently, the nutritional value could be degraded. Seafood, such as fish, shellfish, and seaweed, could be considered as one of the main iodine sources. The deficient or excessive consumption of iodine could cause dysfunction and pathologies related to the thyroid gland. The main objective of this work is to evaluated iodine stability in hake (Merluccius) undergone different culinary techniques. The culinary process considered were: boiling, steaming, microwave cooking, baking, cooking en papillote (twisted cover with the shape of a sweet wrapper) and coating with a batter of flour and deep-frying. The determination of iodine was carried by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Regarding sample handling strategies, liquid-liquid extraction has demonstrated to be a powerful pre-concentration and clean-up approach for trace metal analysis by ICP techniques. Extraction with tetramethylammonium hydroxide (TMAH reagent) was used as a sample preparation method in this work. Based on the results, it can be concluded that the stability of iodine was degraded with the cooking processes. The major degradation was observed for the boiling and microwave cooking processes. The content of iodine in hake decreased up to 60% and 52%, respectively. However, if the boiling cooking liquid is preserved, this loss that has been generated during cooking is reduced. Only when the fish was cooked by following the cooking en papillote process the iodine content was preserved.

Keywords: cooking process, ICP-MS, iodine, hake

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Authors: Sina Abadzadesahraei, Stephen Déry, John Rex

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Climate research has repeatedly identified strong associations between anthropogenic emissions of ‘greenhouses gases’ and observed increases of global mean surface air temperature over the past century. Studies have also demonstrated that the degree of warming varies regionally. Canada is not exempt from this situation, and evidence is mounting that climate change is beginning to cause diverse impacts in both environmental and socio-economic spheres of interest. For example, northeastern British Columbia (BC), whose climate is controlled by a combination of maritime, continental and arctic influences, is warming at a greater rate than the remainder of the province. There are indications that these changing conditions are already leading to shifting patterns in the region’s hydrological cycle, and thus its available water resources. Coincident with these changes, northeastern BC is undergoing rapid development for oil and gas extraction: This depends largely on subsurface hydraulic fracturing (‘fracking’), which uses enormous amounts of freshwater. While this industrial activity has made substantial contributions to regional and provincial economies, it is important to ensure that sufficient and sustainable water supplies are available for all those dependent on the resource, including ecological systems. In this turn demands a comprehensive understanding of how water in all its forms interacts with landscapes, the atmosphere, and of the potential impacts of changing climatic conditions on these processes. The aim of this study is therefore to characterize and quantify all components of the water budget in the small watershed of Coles Lake (141.8 km², 100 km north of Fort Nelson, BC), through a combination of field observations and numerical modelling. Baseline information will aid the assessment of the sustainability of current and future plans for freshwater extraction by the oil and gas industry, and will help to maintain the precarious balance between economic and environmental well-being. This project is a perfect example of interdisciplinary research, in that it not only examines the hydrology of the region but also investigates how natural gas operations and growth can affect water resources. Therefore, a fruitful collaboration between academia, government and industry has been established to fulfill the objectives of this research in a meaningful manner. This project aims to provide numerous benefits to BC communities. Further, the outcome and detailed information of this research can be a huge asset to researchers examining the effect of climate change on water resources worldwide.

Keywords: northeastern British Columbia, water resources, climate change, oil and gas extraction

Procedia PDF Downloads 264

Authors: Mona Hejazi, Ali Motie Nasrabadi

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Epilepsy is a persistent neurological disorder that affects more than 50 million people worldwide. Hence, there is a necessity to introduce an efficient prediction model for making a correct diagnosis of the epileptic seizure and accurate prediction of its type. In this study we consider how the Effective Connectivity (EC) patterns obtained from intracranial Electroencephalographic (EEG) recordings reveal information about the dynamics of the epileptic brain and can be used to predict imminent seizures, as this will enable the patients (and caregivers) to take appropriate precautions. We use this definition because we believe that effective connectivity near seizures begin to change, so we can predict seizures according to this feature. Results are reported on the standard Freiburg EEG dataset which contains data from 21 patients suffering from medically intractable focal epilepsy. Six channels of EEG from each patients are considered and effective connectivity using Directed Transfer Function (DTF) and Granger Causality (GC) methods is estimated. We concentrate on effective connectivity standard deviation over time and feature changes in five brain frequency sub-bands (Alpha, Beta, Theta, Delta, and Gamma) are compared. The performance obtained for the proposed scheme in predicting seizures is: average prediction time is 50 minutes before seizure onset, the maximum sensitivity is approximate ~80% and the false positive rate is 0.33 FP/h. DTF method is more acceptable to predict epileptic seizures and generally we can observe that the greater results are in gamma and beta sub-bands. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices.

Keywords: effective connectivity, Granger causality, directed transfer function, epilepsy seizure prediction, EEG

Procedia PDF Downloads 469

Authors: Prima Luna, Afroditi Chatzifragkou, Dimitris Charalampopoulos

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Sorghum byproducts, namely bran, stalk, and panicle are examples of lignocellulosic biomass. These raw materials contain large amounts of polysaccharides, in particular hemicelluloses, celluloses, and lignins, which if efficiently extracted, can be utilised for the development of a range of added value products with potential applications in agriculture and food packaging sectors. The aim of this study was to characterise fractions extracted from sorghum bran and stalk with regards to their physicochemical properties that could determine their applicability as food-packaging materials. A sequential alkaline extraction was applied for the isolation of cellulosic, hemicellulosic and lignin fractions from sorghum stalk and bran. Lignin content, phenolic content and antioxidant capacity were also investigated in the case of the lignin fraction. Thermal analysis using differential scanning calorimetry (DSC) and X-Ray Diffraction (XRD) revealed that the glass transition temperature (T_g) of cellulose fraction of the stalk was ~78.33 ^oC at amorphous state (~65%) and water content of ~5%. In terms of hemicellulose, the T_g value of stalk was slightly lower compared to bran at amorphous state (~54%) and had less water content (~2%). It is evident that hemicelluloses generally showed a lower thermal stability compared to cellulose, probably due to their lack of crystallinity. Additionally, bran had higher arabinose-to-xylose ratio (0.82) than the stalk, a fact that indicated its low crystallinity. Furthermore, lignin fraction had T_g value of ~93 ^oC at amorphous state (~11%). Stalk-derived lignin fraction contained more phenolic compounds (mainly consisting of p-coumaric and ferulic acid) and had higher lignin content and antioxidant capacity compared to bran-derived lignin fraction.

Keywords: alkaline extraction, bran, cellulose, hemicellulose, lignin, stalk

Procedia PDF Downloads 300

Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

Procedia PDF Downloads 39

Authors: Hongjian Jia

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A finite-length cylindrical shell with a spherical cap is a typical engineering approximation model of actual underwater targets. The research on the omni-directional acoustic scattering characteristics of this target model can provide a favorable basis for the detection and identification of actual underwater targets. The elastic resonance characteristics of the target are the results of the comprehensive effect of the target length, shell-thickness ratio and materials. Under the conditions of different materials and geometric dimensions, the coincidence resonance characteristics of the target have obvious differences. Aiming at this problem, this paper obtains the omni-directional acoustic scattering field of the underwater hemispherical cylindrical shell by numerical calculation and studies the influence of target geometric parameters (length, shell-thickness ratio) and material parameters on the coincidence resonance characteristics of the target in turn. The study found that the formant interval is not a stable value and changes with the incident angle. Among them, the formant interval is less affected by the target length and shell-thickness ratio and is significantly affected by the material properties, which is an effective feature for classifying and identifying targets of different materials. The quadratic polynomial is utilized to fully fit the change relationship between the formant interval and the angle. The results show that the three fitting coefficients of the stainless steel and aluminum targets are significantly different, which can be used as an effective feature parameter to characterize the target materials.

Keywords: hemispherical cylindrical shell;, fine echo characteristics;, geometric and material parameters;, formant interval

Procedia PDF Downloads 111

Authors: Iman A. Saad, Loay E. George

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Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

Procedia PDF Downloads 336

Authors: A. Abdi, A. Abbasi Daloee, A. Barari

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Aim: The adaptations that occur in human body after doing exercises training are a factor to help healthy people stay away from certain diseases. One of the main adaptations is a change in blood circulation, especially in vessels. The increase of capillary density is dependent on the balance between angiogenic and angiostatic factors. Most studies show that the changes made to angiogenic developmental factors resulted from physical exercises indicate the low level of stimulators compared with inhibitors. It is believed that the plasma level of VEGF-A, the important angiogenic factor, is reduced after physical exercise. Findings indicate that the extract of crataegus plant reduces the platelet-derived growth factor receptor (PDGFR) autophosphorylation in human's fibroblast. More importantly, crataegus (1 to 100 mg in liter) clearly leads to the inhibition of PDGFR autophosphorylation in vascular smooth muscle cells (VSMCs). Angiogenesis is a process that can be classified into physiological and pathophysiological forms. collagen XVIII is a part of extracellular protein and heparan sulfate proteoglycans in vascular epithelial and endothelial basement membrane cause the release of endostatin from noncollagenous collagen XVIII. Endostatin inhibits the growth of endothelial cells, inhibits angiogenesis, weakens different types of cancer, and the growth of tumors. The purpose of the current study was to investigate the effect of intensive aerobic running with or without aqueous extraction of black Crataegus elbursensis on Collagen XVIII in male rats. Design: Thirty-two Wistar male rats (4-6 weeks old, 125-135 gr weight) were acquired from the Pasteur's Institute (Amol, Mazandaran), and randomly assigned into control (n = 16) and training (n = 16) groups. Rats were further divided into saline-control (SC) (n=8), saline-training (ST) (n=8), crataegus pentaegyna extraction -control (CPEC) (n=8), and crataegus pentaegyna extraction - training (CPET) (n=8). The control (SC and CPEC) groups remained sedentary; whereas the training groups underwent a high running exercise program. plasma were excised and immediately frozen in liquid nitrogen. Statistical analysis was performed using a one way analysis of variance and Tukey test. Significance was accepted at P = 0.05. Results: The results show that aerobic exercise group had the highest concentration collagen XVIII compared to other groups and then respectively black crataegus, training-crataegus and control groups. Conclusion: In general, researchers in this study concluded that the increase of collagen XVIII (albeit insignificant) as a result of physical activity and consumption of black crataegus extract could possibly serve as a regional inhibitor of angiogenesis and another evidence for the anti-cancer effects of physical activities. Since the research has not managed in this study to measure the amount of plasma endostatin, it is suggested that both indices are measured with important angiogenic factors so that we can have a more accurate interpretation of changes to angiogenic and angiostatic factors resulted from physical exercises.

Keywords: aerobic running, Crataegus elbursensis, Collagen XVIII

Procedia PDF Downloads 325

Authors: Fangyan Li, Lin Min Lee, Hui Zhu Peh, Shoet Harn Chan

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Advantame, a derivative of aspartame, is the latest addition to a family of low caloric and high potent dipeptide sweeteners which include aspartame, neotame and alitame. The use of advantame as a high-intensity sweetener in food was first accepted by Food Standards Australia New Zealand in 2011 and subsequently by US and EU food authorities in 2014, with the results from toxicity and exposure studies showing advantame poses no safety concern to the public at regulated levels. To our knowledge, currently there is barely any detailed information on the analytical method of advantame in food matrix, except for one report published in Japanese, stating a high performance liquid chromatography (HPLC) and liquid chromatography/ mass spectrometry (LC-MS) method with a detection limit at ppm level. However, the use of acid in sample preparation and instrumental analysis in the report raised doubt over the reliability of the method, as there is indication that stability of advantame is compromised under acidic conditions. Besides, the method may not be suitable for analyzing food matrices containing advantame at low ppm or sub-ppm level. In this presentation, a simple, specific and sensitive method for the determination of advantame in food is described. The method involved extraction with water and clean-up via solid phase extraction (SPE) followed by detection using liquid chromatography tandem mass spectrometry (LC-MS/MS) in negative electrospray ionization mode. No acid was used in the entire procedure. Single laboratory validation of the method was performed in terms of linearity, precision and accuracy. A low detection limit at ppb level was achieved. Satisfactory recoveries were obtained using spiked samples at three different concentration levels. This validated method could be used in the routine inspection of the advantame level in food.

Keywords: advantame, food, LC-MS/MS, sweetener

Procedia PDF Downloads 477

Authors: Kyoungrean Kim

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Importance of deep-sea mineral resources is dramatically increasing due to the depletion of land mineral resources corresponding to increasing human’s economic activities. Korea has acquired exclusive exploration licenses at four areas which are the Clarion-Clipperton Fracture Zone in the Pacific Ocean (2002), Tonga (2008), Fiji (2011) and Indian Ocean (2014). The preparation for commercial mining of Nautilus minerals (Canada) and Lockheed martin minerals (USA) is expected by 2020. The London Protocol 1996 (LP) under International Maritime Organization (IMO) and International Seabed Authority (ISA) will set environmental guidelines for deep-sea mining until 2020, to protect marine environment. In this research, the applicability of washing/extraction treatment for the remediation of deep-sea mining tailings was mainly evaluated in order to present preliminary data to develop practical remediation technology in near future. Polymetallic nodule samples were collected at the Clarion-Clipperton Fracture Zone in the Pacific Ocean, then stored at room temperature. Samples were pulverized by using jaw crusher and ball mill then, classified into 3 particle sizes (> 63 µm, 63-20 µm, < 20 µm) by using vibratory sieve shakers (Analysette 3 Pro, Fritsch, Germany) with 63 µm and 20 µm sieve. Only the particle size 63-20 µm was used as the samples for investigation considering the lower limit of ore dressing process which is tens to 100 µm. Rhamnolipid and sodium alginate as biosurfactant and aluminum sulfate which are mainly used as flocculant were used as environmentally friendly additives. Samples were adjusted to 2% liquid with deionized water then mixed with various concentrations of additives. The mixture was stirred with a magnetic bar during specific reaction times and then the liquid phase was separated by a centrifugal separator (Thermo Fisher Scientific, USA) under 4,000 rpm for 1 h. The separated liquid was filtered with a syringe and acrylic-based filter (0.45 µm). The extracted heavy metals in the filtered liquid were then determined using a UV-Vis spectrometer (DR-5000, Hach, USA) and a heat block (DBR 200, Hach, USA) followed by US EPA methods (8506, 8009, 10217 and 10220). Polymetallic nodule was mainly composed of manganese (27%), iron (8%), nickel (1.4%), cupper (1.3 %), cobalt (1.3%) and molybdenum (0.04%). Based on remediation standards of various countries, Nickel (Ni), Copper (Cu), Cadmium (Cd) and Zinc (Zn) were selected as primary target materials. Throughout this research, the use of rhamnolipid was shown to be an effective approach for removing heavy metals in samples originated from manganese nodules. Sodium alginate might also be one of the effective additives for the remediation of deep-sea mining tailings such as polymetallic nodules. Compare to the use of rhamnolipid and sodium alginate, aluminum sulfate was more effective additive at short reaction time within 4 h. Based on these results, sequencing particle separation, selective extraction/washing, advanced filtration of liquid phase, water treatment without dewatering and solidification/stabilization may be considered as candidate technologies for the remediation of deep-sea mining tailings.

Keywords: deep-sea mining tailings, heavy metals, remediation, extraction, additives

Procedia PDF Downloads 157

Authors: Wajih Abbassi, Zouhaier Ben Khelifa

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The present research points towards the empirical validation of three options valuation models, the ad-hoc Black-Scholes model as proposed by Berkowitz (2001), the constant elasticity of variance model of Cox and Ross (1976) and the Kou jump-diffusion model (2002). Our empirical analysis has been conducted on a sample of 26,974 options written on three indexes, the S&P 500, Nasdaq 100 and the Russell 2000 that were negotiated during the year 2007 just before the sub-prime crisis. We start by presenting the theoretical foundations of the models of interest. Then we use the technique of trust-region-reflective algorithm to estimate the structural parameters of these models from cross-section of option prices. The empirical analysis shows the superiority of the Kou jump-diffusion model. This superiority arises from the ability of this model to portray the behavior of market participants and to be closest to the true distribution that characterizes the evolution of these indices. Indeed the double-exponential distribution covers three interesting properties that are: the leptokurtic feature, the memory less property and the psychological aspect of market participants. Numerous empirical studies have shown that markets tend to have both overreaction and under reaction over good and bad news respectively. Despite of these advantages there are not many empirical studies based on this model partly because probability distribution and option valuation formula are rather complicated. This paper is the first to have used the technique of nonlinear curve-fitting through the trust-region-reflective algorithm and cross-section options to estimate the structural parameters of the Kou jump-diffusion model.

Keywords: jump-diffusion process, Kou model, Leptokurtic feature, trust-region-reflective algorithm, US index options

Procedia PDF Downloads 429

Authors: Mariam Dianat Sabet Gilani, Lars M. Blank, Birgitta E. Ebert

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Plant-derived lupane-type, pentacyclic triterpenoids are biologically active compounds that are highly interesting for applications in medical, pharmaceutical, and cosmetic industries. Due to the low abundance of these valuable compounds in their natural sources, and the environmentally harmful downstream process, alternative production methods, such as microbial cell factories, are investigated. Engineered Saccharomyces cerevisiae strains, harboring the heterologous genes for betulinic acid synthesis, can produce up to 2 g L-1 triterpenoids, showing high potential for large-scale production of triterpenoids. One limitation of the microbial synthesis is the intracellular product accumulation. It not only makes cell disruption a necessary step in the downstream processing but also limits productivity and product yield per cell. To overcome these restrictions, the aim of this study is to develop an in-situ extraction method, which extracts triterpenoids into a second organic phase. Such a continuous or sequential product removal from the biomass keeps the cells in an active state and enables extended production time or biomass recycling. After screening of twelve different solvents, selected based on product solubility, biocompatibility, as well as environmental and health impact, isopropyl myristate (IPM) was chosen as a suitable solvent for in-situ product removal from S. cerevisiae. Impedance-based single-cell analysis and off-gas measurement of carbon dioxide emission showed that cell viability and physiology were not affected by the presence of IPM. Initial experiments demonstrated that after the addition of 20 vol % IPM to cultures in the stationary phase, 40 % of the total produced triterpenoids were extracted from the cells into the organic phase. In future experiments, the application of IPM in a repeated batch process will be tested, where IPM is added at the end of each batch run to remove triterpenoids from the cells, allowing the same biocatalysts to be used in several sequential batch steps. Due to its high biocompatibility, the amount of IPM added to the culture can also be increased to more than 20 vol % to extract more than 40 % triterpenoids in the organic phase, allowing the cells to produce more triterpenoids. This highlights the potential for the development of a continuous large-scale process, which allows biocatalysts to produce intracellular products continuously without the necessity of cell disruption and without limitation of the cell capacity.

Keywords: betulinic acid, biocompatible solvent, in-situ extraction, isopropyl myristate, process development, secondary metabolites, triterpenoids, yeast

Procedia PDF Downloads 153