Search results for: soxhlet extraction

Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

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Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

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Authors: Nawel Boucherba, Azzedine Bettache, Abdelaziz Messis, Francis Duchiron, Said Benallaoua

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The impetus for research in the field of bioseparation has been sparked by the difficulty and complexity in the downstream processing of biological products. Indeed, 50% to 90% of the production cost for a typical biological product resides in the purification strategy. There is a need for efficient and economical large scale bioseparation techniques which will achieve high purity and high recovery while maintaining the biological activity of the molecule. One such purification technique which meets these criteria involves the partitioning of biomolecules between two immiscible phases in an aqueous system (ATPS). The Production of xylanases is carried out in 500ml of a liquid medium based on birchwood xylan. In each ATPS, PEG 1000 is added to a mixture consisting of dipotassium phosphate, sodium chloride and the culture medium inoculated with the strain Jonesia denitrificans, the mixture was adjusted to different pH. The concentration of PEG 1000 was varied: 8 to 16 % and the NaCl percentages are also varied from 2 to 4% while maintaining the other parameters constant. The results showed that the best ATPS for purification of xylanases is composed of PEG 1000 at 8.33%, 13.14 % of K2HPO4, 1.62% NaCl at pH 7. We obtained a yield of 96.62 %, a partition coefficient of 86.66 and a purification factor of 2.9. The zymogram showed that the activity is mainly detected in the top phase.

Keywords: Jonesia denitrificans BN13, xylanase, aqueous two phases system, zymogram

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

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Authors: Ayse Demirbas, Bruce A. Welt, Yavuz Yagiz

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Oxidation of polyunsaturated fatty acids (PUFA), eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in fish causes loss of product quality. Oxidative rancidity causes loss of nutritional value and undesirable color changes. Therefore, powerful antioxidant extracts may provide a relatively low cost and natural means to reduce oxidation, resulting in longer, higher quality and higher value shelf life of foods. In this study, we measured effects of red cabbage antioxidant on lipid oxidation in fresh tilapia filets using thiobarbituric acid reactive substances (TBARS) assay, peroxide value (PV) and color assesment analysis. Extraction of red cabbage was performed using an efficient microwave method. Fresh tilapia filets were dipped in or sprayed with solutions containing different concentrations of extract. Samples were stored for up to 9 days at 4°C and analyzed every other day for color and lipid oxidation. Results showed that treated samples had lower oxidation than controls. Lipid peroxide values on treated samples showed benefits through day-7. Only slight differences were observed between spraying and dipping methods. This work shows that red cabbage antioxidant extracts may represent an inexpensive and all natural method for reducing oxidative spoilage of fresh fish.

Keywords: antioxidant, shelf life, fish, red cabbage, lipid oxidation

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Authors: M. D. H. Beg, John O. Akindoyo, Suriati Ghazali, Nitthiyah Jeyaratnam

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Over the period of time, several approaches have been undertaken to mitigate the challenges associated with bone regeneration. This includes but not limited to xenografts, allografts, autografts as well as artificial substitutions like bioceramics, synthetic cements and metals. The former three techniques often come along with peculiar limitation and problems such as morbidity, availability, disease transmission, collateral site damage or absolute rejection by the body as the case may be. Synthetic routes remain the only feasible alternative option for treatment of bone defects. Hydroxyapatite (HA) is very compatible and suitable for this application. However, most of the common methods for HA synthesis are either expensive, complicated or environmentally unfriendly. Interestingly, extraction of HA from bio-wastes have been perceived not only to be cost effective, but also environment friendly. In this research, HA was synthesized from bio-waste: namely bovine bones through three different methods which are hydrothermal chemical processes, ultrasound assisted synthesis and ordinary calcination techniques. Structure and property analysis of the HA was carried out through different characterization techniques such as TGA, FTIR, and XRD. All the methods applied were able to produce HA with similar compositional properties to biomaterials found in human calcified tissues. Calcination process was however observed to be more efficient as it eliminated all the organic components from the produced HA. The HA synthesized is unique for its minimal cost and environmental friendliness. It is also perceived to be suitable for tissue and bone engineering applications.

Keywords: hydroxyapatite, bone, calcination, biowaste

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Authors: Shan-Ying Wu, Sheng-Hui Lan, Xi-Zhang Lin, Ih-Jen Su, Ting-Fen Tsai, Chia-Jui Yen, Tsung-Hsueh Lu, Fu-Wen Liang, Huey-Jen Su, Chun-Li Su, Hsiao-Sheng Liu

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In hepatocelluar carcinoma (HCC), dysregulated expression of cyclin D1 and impaired autophagy has been reported separately. However, the relationship between them has not been explored. In this study, we demonstrated that autophagy was inversely correlated with cyclin D1 expression in 147 paired HCC patient specimens. HCC specimen with highly expression of cyclin D1 shows correlation with poor overall survival rate. Furthermore, induction of autophagy by amiodarone (antiarrhythmic drug) in Hep 3B cells, cyclin D1 was recruited into autophagosomes demonstrated by immune-gold labeling of cyclin D1 after extraction of autophagosomes. We further demonstrated that autophagy suppresses Hep 3B cell proliferation, and further analysis revealed that cell cycle was arrested at G1 phase. The interaction between LC3 (maker of autophagy) and cyclin D1 was increased after autophagy induction. In addition, ubiquitinated-cyclin D1 was also increased after autophagy induction, which is selectively degraded by autophagosome through binding with SQSTM1/p62 (an adaptor protein). In vivo study showed that amiodarone induced autophagy suppresses liver tumor formation in xenograft mouse and orthotopic rat model through decreasing cyclin D1 expression and inhibition of cell proliferation. Altogether, we reveal a novel mechanism that ubiquitinated cyclin D1 degraded by autophagic pathway by p62 and amiodarone is a promising drug for targeting cyclin D1 in liver cancer therapy.

Keywords: autophagy, cyclin D1, hepatocellular carcinoma, amiodarone

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Authors: Hao Liu, Lihui Zheng, Chinedu J. Okere, Chao Wang, Xiangchun Wang, Peng Zhang

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The coalbed methane (CBM) extraction industry (an unconventional energy source) is yet to promulgated an established standard code of practice for the experimental evaluation of sensitivity damage of coal samples. The existing experimental process of previous researches mainly followed the industry standard for conventional oil and gas reservoirs (CIS). However, the existing evaluation method ignores certain critical differences between CBM reservoirs and conventional reservoirs, which could inevitably result in an inaccurate evaluation of sensitivity damage and, eventually, poor decisions regarding the formulation of formation damage prevention measures. In this study, we propose improved experimental guidelines for evaluating seepage sensitivity damage of CBM reservoirs by leveraging on the shortcomings of the existing methods. The proposed method was established via a theoretical analysis of the main drawbacks of the existing methods and validated through comparative experiments. The results show that the proposed evaluation technique provided reliable experimental results that can better reflect actual reservoir conditions and correctly guide future development of CBM reservoirs. This study is pioneering the research on the optimization of experimental parameters for efficient exploration and development of CBM reservoirs.

Keywords: coalbed methane, formation damage, permeability, unconventional energy source

Procedia PDF Downloads 127

Authors: M. Cuevas-González, O. Monserrat, A. Barra, C. Reyes-Carmona, R.M. Mateos, J. P. Galve, R. Sarro, M. Cantalejo, E. Peña, M. Martínez-Corbella, J. A. Luque, J. M. Azañón, A. Millares, M. Béjar, J. A. Navarro, L. Solari

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Geohazard prone areas require continuous monitoring to detect risks, understand the phenomena occurring in those regions and prevent disasters. Satellite interferometry (InSAR) has come to be a trustworthy technique for ground movement detection and monitoring in the last few years. InSAR based techniques allow to process large areas providing high number of displacement measurements at low cost. However, the results provided by such techniques are usually not easy to interpret by non-experienced users hampering its use for decision makers. This work presents a set of tools developed in the framework of different projects (Momit, Safety, U-Geohaz, Riskcoast) and an example of their use in the Granada Coastal area (Spain) is shown. The ADA (Active Displacement Areas) tool have been developed with the aim of easing the management, use and interpretation of InSAR based results. It provides a semi-automatic extraction of the most significant ADAs through the application ADAFinder tool. This tool aims to support the exploitation of the European Ground Motion Service (EU-GMS), which will provide consistent, regular and reliable information regarding natural and anthropogenic ground motion phenomena all over Europe.

Keywords: ground displacements, InSAR, natural hazards, satellite imagery

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Authors: Alireza Bahramian

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High-purity TiO₂ nanoparticles (NPs) with size ranging between 50 nm and 100 nm are synthesized from titanium slag through sulphate route under sonochemical procedure. The effect of dissolution parameters such as the sulfuric acid/slag weight ratio, caustic soda concentration, digestion temperature and time, and initial particle size of the dried slag on the extraction efficiency of TiO₂ and removal of iron are examined. By optimizing the digestion conditions, a rutile TiO₂ powder with surface area of 42 m²/g and mean pore diameter of 22.4 nm were prepared. A thermo-kinetic analysis showed that the digestion temperature has an important effect, while the acid/slag weight ratio and initial size of the slag has a moderate effect on the dissolution rate. The shrinking-core model including both chemical surface reaction and surface diffusion is used to describe the leaching process. A low value of activation energy, 38.12 kJ/mol, indicates the surface chemical reaction model is a rate-controlling step. The kinetic analysis suggested a first order reaction mechanism with respect to the acid concentrations.

Keywords: TiO₂ nanoparticles, titanium slag, dissolution rate, sonochemical method, thermo-kinetic study

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Authors: Ke He, Wumaier Parezhati, Haruka Yamashita

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Recently, online marketplaces in the e-commerce industry, such as Rakuten and Alibaba, have become some of the most popular online marketplaces in Asia. In these shopping websites, consumers can select purchase products from a large number of stores. Additionally, consumers of the e-commerce site have to register their name, age, gender, and other information in advance, to access their registered account. Therefore, establishing a method for analyzing consumer preferences from both the store and the product side is required. This study uses the Doc2Vec method, which has been studied in the field of natural language processing. Doc2Vec has been used in many cases to analyze the extraction of semantic relationships between documents (represented as consumers) and words (represented as products) in the field of document classification. This concept is applicable to represent the relationship between users and items; however, the problem is that one more factor (i.e., shops) needs to be considered in Doc2Vec. More precisely, a method for analyzing the relationship between consumers, stores, and products is required. The purpose of our study is to combine the analysis of the Doc2vec model for users and shops, and for users and items in the same feature space. This method enables the calculation of similar shops and items for each user. In this study, we derive the real data analysis accumulated in the online marketplace and demonstrate the efficiency of the proposal.

Keywords: Doc2Vec, online marketplace, marketing, recommendation systems

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Authors: Noor Shafifiyaz Mohd Yazid, Najihah Mohd Hashim, Hapipah Mohd Ali, Syam Mohan, Rosea Go

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Artocarpus kemando is a plant species from Moraceae family. This plant is used as household utensil by the local and the fruits are edible. The plants’ bark was used for the extraction process and yielded the chloroform crude extract which was used to screen for anticancer potential. The cytotoxic effect of the extract on CAOV-3 and WRL 68 cell lines were determined using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide or MTT assays. Qualitative AO/PI assay was performed to confirm the apoptosis and necrosis process. Meanwhile, the measurement of cell loss, nuclear morphology, DNA content, cell membrane permeability, mitochondrial membrane potential changes and cytochrome c release from mitochondria were detected through cytotoxicity 3 assay. In MTT assay, A. kemando inhibited 50% growth of CAOV-3 cells at 27.9 ± 0:03, 20.1± 0:03, 18.21± 0:04 µg/mL after 24, 48 and 72 hour, respectively. The morphology changes can be seen on CAOV-3 with a production of cell membrane blebbing, cromatin condensation and apoptotic bodies. Evaluation of cytotoxicity 3 on CAOV-3 cells after treated with extract resulting loss of mitochondrial membrane potential and release of cytochrome c from mitochondria. The results demonstrated A. kemando has potentially anticancer agent, particularly on human ovarian cancer.

Keywords: anticancer, Artocarpus kemando, ovarian cancer, cytotoxicity

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Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

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Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

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Authors: Nadeem A. Siddique, Mohd Mujeeb, Kahkashan

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Introduction: The objective of the projected work is to study the occurrence of the aflatoxins B1, B2, G1and G2 in remedial plants, exclusively in Delphinium denudatum. The aflatoxins were analysed by high-performance liquid chromatography–tandem quadrupole mass spectrometry with electrospray ionization (HPLC–MS/MS) and immunoaffinity column chromatography were used for extraction and purification of aflatoxins. PDA media was selected for fungal count. Results: A good quality linear relationship was originated for AFB1, AFB2, AFG1 and AFG2 at 1–10 ppb (r > 0.9995). The analyte precision at three different spiking levels was 88.7–109.1 %, by means of low per cent relative standard deviations in each case. Within 5 to7 min aflatoxins can be separated using an Agilent XDB C18-column. We found that AFB1 and AFB2 were not found in D. denudatum. This was reliable through exceptionally low figures of fungal colonies observed after 6 hr of incubation. The developed analytical method is straightforward, be successfully used to determine the aflatoxins. Conclusion: The developed analytical method is straightforward, simple, accurate, economical and can be successfully used to find out the aflatoxins in remedial plants and consequently to have power over the quality of products. The presence of aflatoxin in the plant extracts was interrelated to the least fungal load in the remedial plants examined.

Keywords: aflatoxins, delphinium denudatum, liquid chromatography, mass spectrometry

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Authors: Saidu Dalhat Dansadau, Aykut Karaman

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The integration of photography into architecture was a pivotal point in the journey of architectural representation; photography proved itself useful for the betterment of architecture early on, as well as established itself as a necessary tool in the realm of architecture. The main study this paper was extracted from looked into the inquiry of knowing exactly what are the key picturesque locations/structures in Sultanahmet, Fatih-Istanbul, and how can their spatial distribution and cultural significance be characterized and mapped for urban design and development as well as the secondary objective, of which this paper focuses on, is to “Investigate the role of perception in urban environments and how photography serves as a tool for capturing and conveying the perception of Sultanahmet's picturesque structures/locations”. The study achieved these objectives by utilizing methodologies such as geo-tagged photography, sequential photography, social media metadata extraction, GIS mapping, spatial analysis, and visual analysis, focusing on the historically rich and culturally significant study area of Sultanahmet, Fatih-Istanbul. By looking at potential structures/locations and then dissecting their special distribution and cultural significance, the main study was able to achieve the main objective as well as unveil a more nuanced understanding of the dynamics between photography, architecture, and urban design with respect to perception using sequential photography.

Keywords: perception, architectural photography, picturesque, urban design, Sultanahmet, Istanbul

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Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

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The cultural park of the Tassili, occupying a large area of Algeria, is characterized by a rich vegetative biodiversity to be preserved and managed both in time and space. The management of a large area (case of Tassili), by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information etc.), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Multispectral imaging sensors have been very useful in the last decade in very interesting applications of remote sensing. They can aid in several domains such as the de¬tection and identification of diverse surface targets, topographical details, and geological features. In this work, we try to extract vegetative areas using fusion techniques between data acquired from sensor on-board the Earth Observing 1 (EO-1) satellite and Landsat ETM+ and TM sensors. We have used images acquired over the Oasis of Djanet in the National Park of Tassili in the south of Algeria. Fusion technqiues were applied on the obtained image to extract the vegetative fraction of the different classes of land use. We compare the obtained results in vegetation end member extraction with vegetation indices calculated from both Hyperion and other multispectral sensors.

Keywords: Landsat ETM+, EO1, data fusion, vegetation, Tassili, Algeria

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Authors: Yessengali Ussenbekov, Valery Terletskiy, Orik Zhanserkenova, Shynar Kasymbekova, Indira Beyshova, Aitkali Imanbayev, Almas Serikov

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Currently, there are 46 hereditary diseases afflicting cattle with known molecular genetic diagnostic methods developed for them. Genetic anomalies frequently occur in the Holstein cattle breeds from American and Canadian bloodlines. The data on the incidence of BLAD, CVM, DUMPS and BC autosomal recessive lethal mutations in pedigree animals are discordant, the detrimental allele incidence rates are high for the Holstein cattle breed, whereas the incidence rates of these mutations are low in some breeds or they are completely absent. Data were obtained on the basis of frozen semen of stud bulls. DNA was extracted from the semen with the DNA-Sorb-B extraction kit. The lethal mutation in the genes CD18, SLC35A3, UMP and ASS of Alatau stud bulls (N=124) was detected by polymerase chain reaction and RFLP analysis. It was established that stud bulls of the local Alatau breed were not carriers of the BLAD, CVM, DUMPS, and BC detrimental mutations. However, with a view to preventing the dissemination of hereditary diseases it is recommended to monitor the pedigree stock using molecular genetic methods.

Keywords: PCR, autosomal recessive point mutation, BLAD, CVM, DUMPS, BC, stud bulls

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Authors: S. El Hasini, M. El Azzouzi, M. De Nobili, K. Azim, A. Zouahri

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Soil salinization is one of the most severe environmental hazards which threaten sustainable agriculture in arid and semi-arid regions, including Morocco. In this regard the application of organic matter to saline soil has confirmed its effectiveness. The present study was aimed to examine the effect of humic acid which represent, among others, the important component of organic matter that contributes to reduce soil salinity. In fact, different composts taken from Agadir (Morocco), with different C/N ratio, were tested. After extraction and purification of humic acid, the interaction with Na2CO3 was carried out. The reduction of salinity is calculated as a value expressed in mg Na2CO3 equivalent/g HA. The results showed that humic acid had generally a significant effect on salinity. In that respect, the hypothesis proposed that carboxylic groups of humic acid create bonds with excess sodium in the soil to form a coherent complex which descends by leaching operation. The comparison between composts was based on C/N ratio, it showed that the compost with the lower ratio C/N had the most important effect on salinity reduction, whereas the compost with higher C/N ratio was less effective. The study is attended also to evaluate the quality of each compost by determining the humification index, we noticed that the compost which have the lowest C/N (20) ratio was relatively less stable, where a greater predominance of the humified substances, when the compost with C/N ratio is 35 exhibited higher stability.

Keywords: compost, humic acid, organic matter, salinity

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Authors: Mervet A. El-sherif, Ginat M El-sherif, Kadry H Tolba

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The objective of this study was to determine, identify and investigate the effects of natural antioxidants of licorice and carob. Besides, their effects as powder and antioxidant extracts addition on refined sunflower oil stability as natural antioxidants were evaluated. Total polyphenol contents as total phenols, total carotenoids and total tannins were 353.93mg/100g (gallic acid), 10.62mg/100g (carotenoids) and 83.33mg/100g (tannic acid), respectively in licorice, while in carob, it was 186.07, 18.66 and 106.67, respectively. Polyphenol compounds of the studied licorice and carob extracts were determined and identified by HPLC. The stability of refined sunflower oil (which determined by peroxide value and Rancimat) was increased with increasing the level of polyphenols extracts addition. Also, our study shows the effect of addition of these polyphenols extracts to El-mewled El-nabawy sweets fortified by full cream milk powder (sesames and folia). We found that, licorice and carob as powder and polyphenols extracts were delayed the rancidity of sesame and peanut significantly. That encourages using licorice and carob as powder and polyphenols extracts as a good natural antioxidants source instead of synthetic antioxidants.

Keywords: licorice, carob, natural antioxidants, antioxidant activity, applications

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Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

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Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

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Authors: Musa D. Aliyu, Ouahid Harireche, Colin D. Hills

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The incapability of supercritical C02 to transport and dissolve mineral species from the geothermal reservoir to the fracture apertures and other important parameters in heat mining makes it an attractive substance for Heat extraction from hot dry rock. In other words, the thermodynamic efficiency of hot dry rock (HDR) reservoirs also increases if supercritical C02 is circulated at excess temperatures of 3740C without the drawbacks connected with silica dissolution. Studies have shown that circulation of supercritical C02 in homogenous geothermal reservoirs is quite encouraging; in comparison to that of the water. This paper aims at investigating the aforementioned processes in the case of the heterogeneous geothermal reservoir located at the Soultz site (France). The MultiPhysics finite element package COMSOL with an interface of coupling different processes encountered in the geothermal reservoir stimulation is used. A fully coupled numerical model is developed to study the thermal and hydraulic processes in order to predict the long-term operation of the basic reservoir parameters that give optimum energy production. The results reveal that the temperature of the SCC02 at the production outlet is higher than that of water in long-term stimulation; as the temperature is an essential ingredient in rating the energy production. It is also observed that the mass flow rate of the SCC02 is far more favourable compared to that of water.

Keywords: FEM, HDR, heterogeneous reservoir, stimulation, supercritical C02

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Authors: Sahar Shams

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Coeliac disease (CD) is a widely reported disease particularly in countries with predominant Caucasian populations. It presents with many signs and symptoms including iron deficiency (ID) and iron deficiency anaemia/anaemia (IDA/A). The exact association between ID, IDA/A and CD and how accurate these signs are in diagnosing CD is not fully known. This systematic review was conducted to investigate the accuracy of both ID & IDA/A as a diagnostic indicator for CD and whether it warrants point of care testing. A systematic review was performed looking at studies published in MEDLINE, Embase, Cochrane Library, and Web of Science. QUADAS-2 tool was used to assess risk of bias in each study. ROC curve and forest plots were generated as part of the meta-analysis after data extraction. 16 studies were identified in total, 13 of which were IDA/A studies and 3 ID studies. The prevalence of CD regardless of diagnostic indicator was assumed as 1%. The QUADAS-2 tool indicated most of studies as having high risk of bias. The PPV for CD was higher in those with ID than for those with IDA/A. Meta-analysis showed the overall odds of having CD is 5 times higher in individuals with ID & IDA/A. The ROC curve showed that there is definitely an association between both diagnostic indicators and CD, the association is not a particularly strong one due to great heterogeneity between studies. Whilst an association between IDA/A & ID and coeliac disease was evident, the results were not deemed significant enough to prompt coeliac disease testing in those with IDA/A & ID.

Keywords: anemia, iron deficiency anemia, coeliac disease, point of care testing

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Authors: Zhengkun Yi

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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

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Authors: Franz Zirena Vilca, Nestor Cahui Galarza, Walter Alejandro Zamalloa Cuba, Edith Tello Palma, Teofilo Donaires Flores, Valdemar Luiz Tornisielo

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The production of rainbow trout in the Lake Titicaca represents an important economic activity for Peru. The city of Puno is responsible for 83% of this production, so the use of antibiotics within the aquaculture system is not alien to this reality. Meanwhile, the waters of Lake Titicaca represent an important source for the supply of drinking water for 80% of the population of the Puno city. In this paper, twelve antibiotics for veterinary use were monitored in water samples during two seasons: dry (July 2015) and rainy (February 2016), water samples from trout production systems, near the water catching point in the lake and drinking water in the city house of Puno were considered. The samples were analyzed using liquid chromatography coupled to mass spectrometry and solid online phase extraction (On-line SPE-LC-MS/MS), all samples analyzed showed concentrations of Ciprofloxacin up to 65.2 ng L⁻¹ at the rainy season. On the other hand, 63% of water samples from the dry season and 36 % from the rainy season showed Chlortetracycline up to 8.7 and 6.1 ng L⁻¹, respectively. The presence of residues of veterinary antibiotics in drinking water means a serious health risk for 80% of the population of Puno since all these people are supplied from this source.

Keywords: chromatography, DNA damage, environmental risk, water pollution

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Authors: McKenzie S. Braley, Lesley Jessiman

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If language reveals internal psychological processing, then it is also likely that language use in autobiographical memory transcripts may be used as a window into attachment style and related personality features. The current study, therefore, examined the possible associations between attachment style, negative affectivity, social inhibition, and linguistic features extracted from autobiographical memory transcripts. Young adult participants (n = 61) filled out attachment and personality questionnaires, and orally reported a relationship-related memory. Memories were audio-recorded and later transcribed verbatim. Using a computerized linguistic extraction tool, positive affect words, negative affect words, and cognition words were extracted. Spearman’s rank correlation coefficients revealed that attachment anxiety was negatively correlated with cognition words (r2 = -0.26, p = 0.047) and that negative affectivity was negatively correlated with positive affect words (r2 = -0.32, p = 0.012). The findings suggest that attachment style and personality are associated with speech styles indicative of both emotionality and depth of processing. Because attachment styles, negative affectivity, and social inhibition are associated with poor mental health outcomes, analyses of key linguistics features in autobiographical memory narratives may provide reliable screening tools for mental wellbeing.

Keywords: attachment style, autobiographical memory, language, negative affectivity, social inhibition

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Authors: Rujia Chen, Ajit Narayanan

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Convolutional neural networks (CNN), as typically applied in deep learning, use layer-wise backpropagation (BP) to construct filters and kernels for feature extraction. Such filters are 2D or 3D groups of weights for constructing feature maps at subsequent layers of the CNN and are shared across the entire input. BP as a gradient descent algorithm has well-known problems of getting stuck at local optima. The use of genetic algorithms (GAs) for evolving weights between layers of standard artificial neural networks (ANNs) is a well-established area of neuroevolution. In particular, the use of crossover techniques when optimizing weights can help to overcome problems of local optima. However, the application of GAs for evolving the weights of filters and kernels in CNNs is not yet an established area of neuroevolution. In this paper, a GA-based filter development algorithm is proposed. The results of the proof-of-concept experiments described in this paper show the proposed GA algorithm can find filter weights through evolutionary techniques rather than BP learning. For some simple classification tasks like geometric shape recognition, the proposed algorithm can achieve 100% accuracy. The results for MNIST classification, while not as good as possible through standard filter learning through BP, show that filter and kernel evolution warrants further investigation as a new subarea of neuroevolution for deep architectures.

Keywords: neuroevolution, convolutional neural network, genetic algorithm, filters, kernels

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Authors: Nematollah Gheibi, Nader Divan Khosroshahi, Mahdi Mohammadi Ghanbarlou

Abstract:

Introduction: Nowadays, the phenomenon of bacterial resistance is one of the most important challenge of the health community in the world. Propolis is most important production of bee colonies that collected from of various plants. So far, a lot of investigations carried out about its antibacterial effects. Material and methods: Thirty gram of propolis prepared as ethanolic extract and after different process of purification, 7.5 gr of its pure form were obtained. Propolis compounds identification was performed by TLC and VLC methods. The HPLC spectrum obtaining from propolis ethanolic extract was compared with some purified standard phenolic and flavonoid substances. Antibacterial effects of ethanol extract of purified propolis were evaluated on two strains of Staphylococcus aureus and Pseudomonas aeruginosa and their MIC was determined by the microdillution assay. Results: Ethanolic propolis extraction analyzed by TLC were resulted to confirm several phenolic and flavonoid compounds in this extract and some of the confirmed by HPLC technique. Minimum inhibitory concentration (MIC) for standard Staphylococcus aureus (ATCC25923) and Pseudomonas aeruginosa (ATCC27853) strains were obtained 2.5 mg/ml and 50 mg/ml respectively. Conclusion: Bee Propolis is a mix organic compound that has a lot of beneficial effects such as anti-bacterial that emphasized in this investigation. It is proposed as a rich source of natural phenolic and flavonoids compounds in designing of new biological resources for hygienic and medical applications.

Keywords: propolis, Staphylococcus aureus, Pseudomonas aeruginosa, antibacterial

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Authors: J. P. Reges, L. C. S. Mazza, E. J. Braga, J. A. Bessa, A. R. Alexandria

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This paper proposes the development of control and automation of irrigation system located sunflower harvest in the Teaching Unit, Research and Extension (UEPE), the Apodi Plateau in Limoeiro do Norte. The sunflower extraction, which in turn serves to get the produced oil from its seeds, animal feed, and is widely used in human food. Its nutritional potential is quite high what makes of foods produced from vegetal, very rich and healthy. The focus of research is to make the autonomous irrigation system sunflower crop from programmable logic control energized with alternative energy sources, solar photovoltaics. The application of automated irrigation system becomes interesting when it provides convenience and implements new forms of managements of the implementation of irrigated cropping systems. The intended use of automated addition to irrigation quality and consequently brings enormous improvement for production of small samples. Addition to applying the necessary and sufficient features of water management in irrigation systems, the system (PLC + actuators + Renewable Energy) will enable to manage the quantitative water required for each crop, and at the same time, insert the use of sources alternative energy. The entry of the automated collection will bring a new format, and in previous years, used the process of irrigation water wastage base and being the whole manual irrigation process.

Keywords: automation, control, sunflower, irrigation, programming, renewable energy

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Authors: Nur A. Özdemir, Sude Erkin, Hatice K. Güney, Cemre S. Atılgan, Enes Huylu, Hüseyin Y. Altıntaş, Aysemin Top, Özak Durmuş

Abstract:

Carbon emissions produced during a product’s life cycle, from extraction of raw materials up to waste disposal and market consumption activities are the major contributors to global warming. In the light of the science-based targets (SBT) leading the way to a zero-carbon economy for sustainable growth of the companies, carbon footprint reporting of the purchased goods has become critical for identifying hotspots and best practices for emission reduction opportunities. In line with Ford Otosan's corporate sustainability strategy, research was conducted to evaluate the carbon footprint of purchased products in accordance with Scope 3 of the Greenhouse Gas Protocol (GHG). The purpose of this paper is to develop a systematic and transparent methodology to calculate carbon footprint of the products produced by automotive OEMs (Original Equipment Manufacturers) within the context of automobile supply chain management. To begin with, primary material data were collected through IMDS (International Material Database System) corresponds to company’s three distinct types of vehicles including Light Commercial Vehicle (Courier), Medium Commercial Vehicle (Transit and Transit Custom), Heavy Commercial Vehicle (F-MAX). Obtained material data was classified as metals, plastics, liquids, electronics, and others to get insights about the overall material distribution of produced vehicles and matched to the SimaPro Ecoinvent 3 database which is one of the most extent versions for modelling material data related to the product life cycle. Product life cycle analysis was calculated within the framework of ISO 14040 – 14044 standards by addressing the requirements and procedures. A comprehensive literature review and cooperation with suppliers were undertaken to identify the production methods of parts used in vehicles and to find out the amount of scrap generated during part production. Cumulative weight and material information with related production process belonging the components were listed by multiplying with current sales figures. The results of the study show a key modelling on carbon footprint of products and processes based on a scientific approach to drive sustainable growth by setting straightforward, science-based emission reduction targets. Hence, this study targets to identify the hotspots and correspondingly provide broad ideas about our understanding of how to integrate carbon footprint estimates into our company's supply chain management by defining convenient actions in line with climate science. According to emission values arising from the production phase including raw material extraction and material processing for Ford OTOSAN vehicles subjected in this study, GHG emissions from the production of metals used for HCV, MCV and LCV account for more than half of the carbon footprint of the vehicle's production. Correspondingly, aluminum and steel have the largest share among all material types and achieving carbon neutrality in the steel and aluminum industry is of great significance to the world, which will also present an immense impact on the automobile industry. Strategic product sustainability plan which includes the use of secondary materials, conversion to green energy and low-energy process design is required to reduce emissions of steel, aluminum, and plastics due to the projected increase in total volume by 2030.

Keywords: automotive, carbon footprint, IMDS, scope 3, SimaPro, sustainability

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Authors: O. Smara, H. Dendougui, B. Legseir

Abstract:

Atriplex halimus L. is particularly well adapted to arid and salt-affected areas. In this species, salinity resistance is often attributed to the presence of vesiculated hairs covering leaf surface and containing a large amount of salt. Atriplex halimus L. (Chenopodiaceae) is a perennial shrub native to the Mediterranean basin with excellent tolerance to drought and salinity. The species is present in semiarid to subhumid areas of the north Mediterranean and in arid zones from North Africa and the eastern Mediterranean. The main aim of this study was to identify a medicinal plant used in the Ouargla (Est-southern Algeria) for the treatment of several human pathologies. This plant is an important source for livestock in nitrogenous matter, it is an effective and relatively inexpensive tool in the fight against erosion and desertification and rehabilitation of degraded lands. Phytochemical investigation is applied to the majority of extracts of the powder of the aerial parts of Atriplex halimus L. Different chromatographic methods after liquid-liquid extraction are used; it is the thin layer chromatography (TLC) and paper using multiple systems and chemical revelations. This study followed by an evaluation by the phenol assay the Folin-Ciocalteu method, using gallic acid as a reference for phenols and quercetin for flavonols. Some polar extracts showed an interesting result better than the less polar extracts.

Keywords: Atriples halimus L., chenopodiaceae, flavonoids, phenols

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

Abstract:

In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

Procedia PDF Downloads 45