Search results for: rule extraction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2759

Search results for: rule extraction

869 Application of KL Divergence for Estimation of Each Metabolic Pathway Genes

Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

Abstract:

The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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868 Colloidal Gas Aphron Generated by a Cationic Surfactant as an Alternative Technique to Recovery Natural Colorants from Fermented Broth

Authors: V. C. Santos-Ebinuma, J. F. B. Pereira, M. F. S. Teixeira, A. Pessoa Jr., P. Jauregi

Abstract:

There is worldwide interest in process development for colorants production from natural sources. Microorganisms provide an alternative source of natural colorants which can be produced by cultivation technology and extracted from fermented broth. The aim of the present work was to study the recovery of red colorants from fermented broth of Penicillium purpurogenum DPUA 1275 using the technique of Colloidal Gas Aphrons (CGA); CGA are surfactant-stabilized microbubbles generated by intense stirring of a surfactant solution. CGA were generated by the cationic, hexadecyl trimethyl ammonium bromide (CTAB) surfactant. Firstly, experiments were carried out at different surfactant/fermented broth volumetric ratios (VCGA/VFB, VRATIO) varying between 3 and 18 at pH 6.9. Secondly, the experiments were carried out at VRATIO of 6 and 12 in different pH, namely, 6.9, 8.0, 9.0 and 10.0. The first results of recovery showed that an increase in the VRATIO from 3 to 6 and 12 promoted an increase as recovery as partition coefficient. However, at VRATIO of 18 the lowest partition coefficient was obtained. The best results were achieved at VRATIO of 6 and 12, namely recovery, Re, around 60% and partition coefficient, K, of 2.5 and 3.0 to 6 and 12 VRATIO, respectively. The second set of experiments showed that the pH 9.0 promoted the best results at VRATIO of 12 as follow: Re=70%, K=5.39, proteins and sugar selectivity (SePROT, 3.75 and SeSUGAR, 7.20, respectively). These results indicate that with CTAB the recovery is mainly driven by electrostatic interactions. In conclusion, the results above show that CGA employing a cationic surfactant is a promissory technique and it can be used as the first step of purification to recovery red colorants from fermented broth.

Keywords: liquid-liquid extraction, colloidal gas aphrons, recovery, natural colorants

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867 Automatic Registration of Rail Profile Based Local Maximum Curvature Entropy

Authors: Hao Wang, Shengchun Wang, Weidong Wang

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On the influence of train vibration and environmental noise on the measurement of track wear, we proposed a method for automatic extraction of circular arc on the inner or outer side of the rail waist and achieved the high-precision registration of rail profile. Firstly, a polynomial fitting method based on truncated residual histogram was proposed to find the optimal fitting curve of the profile and reduce the influence of noise on profile curve fitting. Then, based on the curvature distribution characteristics of the fitting curve, the interval search algorithm based on dynamic window’s maximum curvature entropy was proposed to realize the automatic segmentation of small circular arc. At last, we fit two circle centers as matching reference points based on small circular arcs on both sides and realized the alignment from the measured profile to the standard designed profile. The static experimental results show that the mean and standard deviation of the method are controlled within 0.01mm with small measurement errors and high repeatability. The dynamic test also verified the repeatability of the method in the train-running environment, and the dynamic measurement deviation of rail wear is within 0.2mm with high repeatability.

Keywords: curvature entropy, profile registration, rail wear, structured light, train-running

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866 ANOVA-Based Feature Selection and Machine Learning System for IoT Anomaly Detection

Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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865 Assessment of the Standard of Referrals for Extraction of Carious Primary Teeth under General Anaesthetic

Authors: Emma Carr, Jennifer Morrison, Peter Walker

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Background: Due to COVID-19, there was a significant reduction in the number of children being treated under general anaesthetic (GA) within the health board, which led to a backlog of referrals. The referrals were being triaged and added to a waiting list in order of priority -determined by the information given. By implementing a checklist, it is anticipated that at least 70% of referrals will have the majority of the information required to effectively prioritise patients. The gold standard, as defined in ‘Guidelines For The Management Of Children Referred For Dental Extractions Under General Anaesthesia’, indicates that all referrals should mention: (i) Inability of the child to cooperate, (ii) Previously tried anxiety management techniques, (iii) Existence of psychological disorders, (iv) Presence of acute dental infection, (v) Requirement for extractions in multiple quadrants. Method: 130 referrals were examined over three months and compared to the recommended standard. A letter was emailed to referring dentists within Ayrshire & Arran outlining the recommended information to be included within the referral. The second round of data collection was then carried out, which involved an examination of 105 referrals. Results: The first round revealed that only 28% of referrals mentioned at least four defined standards outlined above. Following issuing a checklist to all dentists, this increased to 72%. Conclusion: As many of the children referred for extractions under GA have suffered pain and infection because of dental caries, it is important that delay of treatment is minimised, where possible. The implementation of a standardised checklist has enabled more effective prioritisation of patients.

Keywords: caries, dentistry, general anaesthetic, paediatrics

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864 A Dynamic Solution Approach for Heart Disease Prediction

Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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863 Extraction of Amorphous SiO₂ From Equisetnm Arvense Plant for Synthesis of SiO₂/Zeolitic Imidazolate Framework-8 Nanocomposite and Its Photocatalytic Activity

Authors: Babak Azari, Afshin Pourahmad, Babak Sadeghi, Masuod Mokhtari

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In this work, Equisetnm arvense plant extract was used for preparing amorphous SiO₂. For preparing of SiO₂/zeolitic imidazolate framework-8 (ZIF-8) nanocomposite by solvothermal method, the synthesized SiO₂ was added to the synthesis mixture ZIF-8. The nanocomposite was characterized using a range of techniques. The photocatalytic activity of SiO₂/ZIF-8 was investigated systematically by degrading crystal violet as a cationic dye under Ultraviolet light irradiation. Among synthesized samples (SiO₂, ZIF-8 and SiO₂/ZIF-8), the SiO₂/ZIF-8 exhibited the highest photocatalytic activity and improved stability compared to pure SiO₂ and ZIF-8. As evidenced by Scanning Electron Microscopy and Transmission electron microscopy images, ZIF-8 particles without aggregation are located over SiO₂. The SiO₂ not only provides structured support for ZIF-8 but also prevents the aggregation of ZIF-8 Metal-organic framework in comparison to the isolated ZIF-8. The superior activity of this photocatalyst was attributed to the synergistic effects from SiO₂ owing to (I) an electron acceptor (from ZIF-8) and an electron donor (to O₂ molecules), (II) preventing recombination of electron-hole in ZIF-8, and (III) maximum interfacial contact ZIF-8 with the SiO₂ surface without aggregation or prevent the accumulation of ZIF-8. The results demonstrate that holes (h+) and •O₂- are primary reactive species involved in the photocatalytic oxidation process. Moreover, the SiO₂/ZIF-8 photocatalyst did not show any obvious loss of photocatalytic activity during five-cycle tests, which indicates that the heterostructured photocatalyst was highly stable and could be used repeatedly.

Keywords: nano, zeolit, potocatalist, nanocomposite

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862 Use of a New Multiplex Quantitative Polymerase Chain Reaction Based Assay for Simultaneous Detection of Neisseria Meningitidis, Escherichia Coli K1, Streptococcus agalactiae, and Streptococcus pneumoniae

Authors: Nastaran Hemmati, Farhad Nikkhahi, Amir Javadi, Sahar Eskandarion, Seyed Mahmuod Amin Marashi

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Neisseria meningitidis, Escherichia coli K, Streptococcus agalactiae, and Streptococcus pneumoniae cause 90% of bacterial meningitis. Almost all infected people die or have irreversible neurological complications. Therefore, it is essential to have a diagnostic kit with the ability to quickly detect these fatal infections. The project involved 212 patients from whom cerebrospinal fluid samples were obtained. After total genome extraction and performing multiplex quantitative polymerase chain reaction (qPCR), the presence or absence of each infectious factor was determined by comparing with standard strains. The specificity, sensitivity, positive predictive value, and negative predictive value calculated were 100%, 92.9%, 50%, and 100%, respectively. So, due to the high specificity and sensitivity of the designed primers, they can be used instead of bacterial culture that takes at least 24 to 48 hours. The remarkable benefit of this method is associated with the speed (up to 3 hours) at which the procedure could be completed. It is also worth noting that this method can reduce the personnel unintentional errors which may occur in the laboratory. On the other hand, as this method simultaneously identifies four common factors that cause bacterial meningitis, it could be used as an auxiliary method diagnostic technique in laboratories particularly in cases of emergency medicine.

Keywords: cerebrospinal fluid, meningitis, quantitative polymerase chain reaction, simultaneous detection, diagnosis testing

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861 Arsenic Speciation in Cicer arietinum: A Terrestrial Legume That Contains Organoarsenic Species

Authors: Anjana Sagar

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Arsenic poisoned ground water is a major concern in South Asia. The arsenic enters the food chain not only through drinking but also by using arsenic polluted water for irrigation. Arsenic is highly toxic in its inorganic forms; however, organic forms of arsenic are comparatively less toxic. In terrestrial plants, inorganic form of arsenic is predominantly found; however, we found that significant proportion of organic arsenic was present in root and shoot of a staple legume, chickpea (Cicer arientinum L) plants. Chickpea plants were raised in pot culture on soils spiked with arsenic ranging from 0-70 mg arsenate per Kg soil. Total arsenic concentrations of chickpea shoots and roots were determined by inductively coupled plasma-mass-spectrometry (ICP-MS) ranging from 0.76 to 20.26, and 2.09 to 16.43 µg g⁻¹ dry weight, respectively. Information on arsenic species was acquired by methanol/water extraction method, with arsenic species being analyzed by high-performance liquid chromatography (HPLC) coupled with ICP-MS. Dimethylarsinic acid (DMA) was the only organic arsenic species found in amount from 0.02 to 3.16 % of total arsenic shoot concentration and 0 to 6.93 % of total arsenic root concentration, respectively. To investigate the source of the organic arsenic in chickpea plants, arsenic species in the rhizosphere of soils of plants were also examined. The absence of organic arsenic in soils would suggest the possibility of formation of DMA in plants. The present investigation provides useful information for better understanding of distribution of arsenic species in terrestrial legume plants.

Keywords: arsenic, arsenic speciation, dimethylarsinic acid, organoarsenic

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860 Bioflocculation Using the Purified Wild Strain of P. aeruginosa Culture in Wastewater Treatment

Authors: Mohammad Hajjartabar, Tahereh Kermani Ranjbar

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P. aeruginosa EF2 was isolated and identified from human infection sources before in our previous study. The present study was performed to determine the characteristics and activity role of bioflocculant produced by the bacterium in flocculation of the wastewater active sludge treatment. The bacterium was inoculated and then was grown in an orbital shaker at 250 rpm for 5 days at 35 °C under TSB and peptone water media. After incubation period, culture broths of the bacterial strain was collected and washed. The concentration of the bacteria was adjusted. For the extraction of the bacterial bioflocculant, culture was centrifuged at 6000 rpm for 20 min at 4 °C to remove bacterial cells. Supernatant was decanted and pellet containing bioflocculant was dried at 105 °C to a constant weight according to APHA, 2005. The chemical composition of the extracted bioflocculant from the bacterial sample was then analyzed. Wastewater active sludge sample obtained from aeration tank from one of wastewater treatment plants in Tehran, was first mixed thoroughly. After addition of bioflocculant, improvements in floc density were observed with an increase in bioflocculant. The results of this study strongly suggested that the extracted bioflucculant played a significant role in flocculation of the wastewater sample. The use of wild bacteria and nutrient regulation techniques instead of genetic manipulation opens wide investigation area in the future to improve wastewater treatment processes. Also this may put a new path in front of us to attain and improve the more effective bioflocculant using the purified microbial culture in wastewater treatment.

Keywords: wastewater treatment, P. aeruginosa, sludge treatment

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859 Assessment of DNA Degradation Using Comet Assay: A Versatile Technique for Forensic Application

Authors: Ritesh K. Shukla

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Degradation of biological samples in terms of macromolecules (DNA, RNA, and protein) are the major challenges in the forensic investigation which misleads the result interpretation. Currently, there are no precise methods available to circumvent this problem. Therefore, at the preliminary level, some methods are urgently needed to solve this issue. In this order, Comet assay is one of the most versatile, rapid and sensitive molecular biology technique to assess the DNA degradation. This technique helps to assess DNA degradation even at very low amount of sample. Moreover, the expedient part of this method does not require any additional process of DNA extraction and isolation during DNA degradation assessment. Samples directly embedded on agarose pre-coated microscopic slide and electrophoresis perform on the same slide after lysis step. After electrophoresis microscopic slide stained by DNA binding dye and observed under fluorescent microscope equipped with Komet software. With the help of this technique extent of DNA degradation can be assessed which can help to screen the sample before DNA fingerprinting, whether it is appropriate for DNA analysis or not. This technique not only helps to assess degradation of DNA but many other challenges in forensic investigation such as time since deposition estimation of biological fluids, repair of genetic material from degraded biological sample and early time since death estimation could also be resolved. With the help of this study, an attempt was made to explore the application of well-known molecular biology technique that is Comet assay in the field of forensic science. This assay will open avenue in the field of forensic research and development.

Keywords: comet assay, DNA degradation, forensic, molecular biology

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858 Machine Learning and Deep Learning Approach for People Recognition and Tracking in Crowd for Safety Monitoring

Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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857 Understanding Cognitive Fatigue From FMRI Scans With Self-supervised Learning

Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

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856 Influence of Ground Granulated Blast Furnace Slag on Geotechnical Characteristics of Jarosite Waste

Authors: Chayan Gupta, Arun Prasad

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The quick evolution of industrialization causes the scarcity of precious land. Thus, it is vital need to influence the R&D societies to achieve sustainable, economic and social benefits from huge utilization of waste for universal aids. The current study promotes the influence of steel industries waste i.e. ground granulated blast furnace slag (GGBS) in geotechnical properties of jarosite waste (solid waste residues produced from hydrometallurgy operations involved in extraction of Zinc). Numerous strengths tests (unconfined compression (qu) and splitting tensile strength (qt)) are conducted on jarosite-GGBS blends (GGBS, 10-30%) with different curing periods (7, 28 & 90 days). The results indicate that both qu and qt increase with the increase in GGBS content along with curing periods. The increased strength with the addition of GGBS is also observed from microstructural study, which illustrates the occurrence of larger agglomeration of jarosite-GGBS blend particles. The Freezing-Thawing (F-T) durability analysis is also conducted for all the jarosite-GGBS blends and found that the reduction in unconfined compressive strength after five successive F-T cycles enhanced from 62% (natural jarosite) to 48, 42 and 34% at 7, 14 and 28 days curing periods respectively for stabilized jarosite-GGBS samples containing 30% GGBS content. It can be concluded from this study that blending of cementing additives (GGBS) with jarosite waste resulted in a significant improvement in geotechnical characteristics.

Keywords: jarosite, GGBS, strength characteristics, microstructural study, durability analysis

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855 Determination of Physicochemical Properties, Bioaccessibility of Phenolics and Antioxidant Capacity of Mineral Enriched Linden Herbal Tea Beverage

Authors: Senem Suna, Canan Ece Tamer, Ömer Utku Çopur

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In this research, dried linden (Tilia argentea) leaves and blossoms were used as a raw material for mineral enriched herbal tea beverage production. For this aim, %1 dried linden was infused with boiling water (100 °C) for 5 minutes. After cooling, sucrose, citric acid, ascorbic acid, natural lemon flavor and natural mineral water were added. Beverage samples were plate filtered, filled into 200-mL glass bottles, capped then pasteurized at 98 °C for 15 minutes. Water soluble dry matter, titratable acidity, ascorbic acid, pH, minerals (Fe, Ca, Mg, K, Na), color (L*, a*, b*), turbidity, bioaccessible phenolics and antioxidant capacity were analyzed. Water soluble dry matter, titratable acidity, and ascorbic were determined as 7.66±0.28 g/100 g, 0.13±0.00 g/100 mL, and 19.42±0.62 mg/100 mL, respectively. pH was measured as 3.69. Fe, Ca, Mg, K and Na contents of the beverage were determined as 0.12±0.00, 115.48±0.05, 34.72±0.14, 48.67±0.43 and 85.72±1.01 mg/L, respectively. Color was measured as 13.63±0.05, -4.33±0.05, and 3.06±0.05 for L*, a*, and b* values. Turbidity was determined as 0.69±0.07 NTU. Bioaccessible phenolics were determined as 312.82±5.91 mg GAE/100 mL. Antioxidant capacities of chemical (MetOH:H2O:HCl) and physiological extracts (in vitro digestive enzymatic extraction) with DPPH (27.59±0.53 and 0.17±0.02 μmol trolox/mL), FRAP (21.01±0.97 and 13.27±0.19 μmol trolox/mL) and CUPRAC (44.71±9.42 and 2.80±0.64 μmol trolox/mL) methods were also evaluated. As a result, enrichment with natural mineral water was proposed for the development of functional and nutritional values together with a good potential for commercialization.

Keywords: linden, herbal tea beverage, bioaccessibility, antioxidant capacity

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854 Polymorphisms of STAT5A and DGAT1 Genes and Their Associations with Milk Trait in Egyptian Goats

Authors: Othman Elmahdy Othman

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The objectives of this study were to identify polymorphisms in the STAT5A using Restriction Fragment Length Polymorphism and DGAT1 using Single-Strand Conformation Polymorphism genes among three Egyptian goat breeds (Barki, Zaraibi, and Damascus) as well as investigate the effect of their genotypes on milk composition traits of Zaraibi goats. One hundred and fifty blood samples were collected for DNA extraction, 60 from Zaraibi, 40 from Damascus and 50 from Barki breeds. Fat, protein and lactose percentages were determined in Zaraibi goat milk using an automatic milk analyzer. Two genotypes, CC and CT (for STAT5A) and C-C- and C-C+ (for DGAT1), were identified in the three Egyptian goat breeds with different frequencies. The associations between these genotypes and milk fat, protein and lactose were determined in Zaraibi breed. The results showed that the STAT5A genotypes had significant effects on milk yield, protein, fat and lactose with the superiority of CT genotype over CC. Regarding DGAT1 polymorphism, the result showed the only association between it with milk fat where the animals with C-C+ genotype had greater milk fat than animals possess C-C- genotype. The association of combined genotypes with milk trait declared that the does with heterozygous genotypes for both genes are preferred than does with homozygous genotypes where the animals with CTC-C+ have more milk yield, fat and protein than those with CCC-C- genotype. In conclusion, the result showed that C/T and C-/C+ SNPs of STAT5A and DGAT1 genes respectively may be useful markers for assisted selection programs to improve goat milk composition

Keywords: DGAT1, genetic polymorphism, milk trait, STAT5A

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853 Deep Feature Augmentation with Generative Adversarial Networks for Class Imbalance Learning in Medical Images

Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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852 The Classification Performance in Parametric and Nonparametric Discriminant Analysis for a Class- Unbalanced Data of Diabetes Risk Groups

Authors: Lily Ingsrisawang, Tasanee Nacharoen

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Introduction: The problems of unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many research papers found that the performance of existing classifier tends to be biased towards the majority class. The k -nearest neighbors’ nonparametric discriminant analysis is one method that was proposed for classifying unbalanced classes with good performance. Hence, the methods of discriminant analysis are of interest to us in investigating misclassification error rates for class-imbalanced data of three diabetes risk groups. Objective: The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification application of class-imbalanced data of diabetes risk groups. Methods: Data from a healthy project for 599 staffs in a government hospital in Bangkok were obtained for the classification problem. The staffs were diagnosed into one of three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data along with the variables; diabetes risk group, age, gender, cholesterol, and BMI was analyzed and bootstrapped up to 50 and 100 samples, 599 observations per sample, for additional estimation of misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples show non-normality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. In finding the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions with three choices of (0.90:0.05:0.05), (0.80: 0.10: 0.10) or (0.70, 0.15, 0.15). Results: The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k = 3 or k = 4 and the prior probabilities of {non-risk:risk:diabetic} as {0.90:0.05:0.05} or {0.80:0.10:0.10} gave the smallest error rate of misclassification. Conclusion: The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: error rate, bootstrap, diabetes risk groups, k-nearest neighbors

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851 New Public Management at Public Administration in Bangladesh: An Exploratory Study

Authors: Biback Das

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New Public Management, a phenomenal tool, which is used to enforcing in public administration in different country’s to enhance the capacities. Since the 1980s, New Public Management (NPM) is primarily focusing to modernize the public sector. From the initial period, many developed countries such as UK, New Zealand, Australia, and the USA are applied in their administration to modernize. Almost 1990s, it has been applied in many developing countries. This study can describe the real situations of NPM based administration. Bangladesh Government has taken many projects to reform the public sector under NPM. Even many Development Agencies like UN, UNDP, World Bank, Asian Development Bank and so on, along with many developed countries also invested and prescribed to take NPM based reform that can to restructure the public sector so that it can maximize the efforts to provide the better service. This study examines using many factors that effects work on Public Administration in Bangladesh and also assessing its endeavor to adopt in it. Although Government has taken such initiatives to implement NPM originated reform, it’s not effectively been implemented to bring positive change about as per NPM objectives. This study mainly examines some initiatives in Bangladesh that have the influence of NPM as well as some drawbacks that can’t help the satisfaction of these initiatives. This article help to identify the efforts of many development agencies providing a fund to enhance the NPM based projects with their specific conditions that are prescribed by them helping to get fund. Therefore, to establish effective public management or to follow NPM model, Bangladesh need having an institutional framework, sound rule of law, proper structure, effective civil service system, appropriate checks, and balances to restructure the public sector help along with donor agencies ad implement in it. Bangladesh Government has applied its recent days to enhance the capabilities in its Public Administration. Moreover, this study mainly identifies how the designing strategies, program formulating, its implementation in various sector such as education, health sector etc. and how to reduce the backdrop the during problem by smooth functioning. This paper is also assessing the influence of many projects like PPP (Public-Private and Partnership) to work along with private organizations for smooth service delivery. Accordingly, this paper briefly reviews how it applies in a global context following the taken many initiatives and the consequences of Bangladesh context.

Keywords: new public management, capacity building, conditionalities, service delivery, public-private-partnership

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850 Mineral Deposits in Spatial Planning Systems – Review of European Practices

Authors: Alicja Kot-Niewiadomska

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Securing sustainable access to raw materials is vital for the growth of the European economy and for the goals laid down in Strategy Europe 2020. One of the most important sources of mineral raw materials are primary deposits. The efficient management of them, including extraction, will ensure competitiveness of the European economy. A critical element of this approach is mineral deposits safeguarding and the most important tool - spatial planning. The safeguarding of deposits should be understood as safeguarding of land access, and safeguarding of area against development, which may (potential) prevent the use of the deposit and the necessary mining activities. Many European Union countries successfully integrated their mineral policy and spatial policy, which has ensured the proper place of mineral deposits in their spatial planning systems. These, in turn, are widely recognized as the most important mineral deposit safeguarding tool, the essence of which is to ensure long-term access to its resources. The examples of Austria, Portugal, Slovakia, Czech Republic, Sweden, and the United Kingdom, discussed in the paper, are often mentioned as examples of good practices in this area. Although none of these countries managed to avoid cases of social and environmental conflicts related to mining activities, the solutions they implement certainly deserve special attention. And for many countries, including Poland, they can be a potential source of solutions aimed at improving the protection of mineral deposits.

Keywords: mineral deposits, land use planning, mineral deposit safeguarding, European practices

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849 Optimization of Multistage Extractor for the Butanol Separation from Aqueous Solution Using Ionic Liquids

Authors: Dharamashi Rabari, Anand Patel

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n-Butanol can be regarded as a potential biofuel. Being resistive to corrosion and having high calorific value, butanol is a very attractive energy source as opposed to ethanol. By fermentation process called ABE (acetone, butanol, ethanol), bio-butanol can be produced. ABE carried out mostly by bacteria Clostridium acetobutylicum. The major drawback of the process is the butanol concentration higher than 10 g/L, delays the growth of microbes resulting in a low yield. It indicates the simultaneous separation of butanol from the fermentation broth. Two hydrophobic Ionic Liquids (ILs) 1-butyl-1-methylpiperidinium bis (trifluoromethylsulfonyl)imide [bmPIP][Tf₂N] and 1-hexyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide [hmim][Tf₂N] were chosen. The binary interaction parameters for both ternary systems i.e. [bmPIP][Tf₂N] + water + n-butanol and [hmim][Tf₂N] + water +n-butanol were taken from the literature that was generated by NRTL model. Particle swarm optimization (PSO) with the isothermal sum rate (ISR) method was used to optimize the cost of liquid-liquid extractor. For [hmim][Tf₂N] + water +n-butanol system, PSO shows 84% success rate with the number of stages equal to eight and solvent flow rate equal to 461 kmol/hr. The number of stages was three with 269.95 kmol/hr solvent flow rate for [bmPIP][Tf₂N] + water + n-butanol system. Moreover, both ILs were very efficient as the loss of ILs in raffinate phase was negligible.

Keywords: particle swarm optimization, isothermal sum rate method, success rate, extraction

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848 Technology in the Calculation of People Health Level: Design of a Computational Tool

Authors: Sara Herrero Jaén, José María Santamaría García, María Lourdes Jiménez Rodríguez, Jorge Luis Gómez González, Adriana Cercas Duque, Alexandra González Aguna

Abstract:

Background: Health concept has evolved throughout history. The health level is determined by the own individual perception. It is a dynamic process over time so that you can see variations from one moment to the next. In this way, knowing the health of the patients you care for, will facilitate decision making in the treatment of care. Objective: To design a technological tool that calculates the people health level in a sequential way over time. Material and Methods: Deductive methodology through text analysis, extraction and logical knowledge formalization and education with expert group. Studying time: September 2015- actually. Results: A computational tool for the use of health personnel has been designed. It has 11 variables. Each variable can be given a value from 1 to 5, with 1 being the minimum value and 5 being the maximum value. By adding the result of the 11 variables we obtain a magnitude in a certain time, the health level of the person. The health calculator allows to represent people health level at a time, establishing temporal cuts being useful to determine the evolution of the individual over time. Conclusion: The Information and Communication Technologies (ICT) allow training and help in various disciplinary areas. It is important to highlight their relevance in the field of health. Based on the health formalization, care acts can be directed towards some of the propositional elements of the concept above. The care acts will modify the people health level. The health calculator allows the prioritization and prediction of different strategies of health care in hospital units.

Keywords: calculator, care, eHealth, health

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847 Investigation of Rifampicin and Isoniazid Resistance Mutated Genes in Mycobacterium Tuberculosis Isolated From Patients

Authors: Seyyed Mohammad Amin Mousavi Sagharchi, Alireza Mahmoudi Nasab, Tim Bakker

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Introduction: Mycobacterium tuberculosis (MTB) is the most intelligent bacterium that existed in the world to our best knowledge. This bacterium can cause tuberculosis (TB) which is responsible for its spread speed and murder of millions of people around the world. MTB has the practical function to escape from anti-tuberculosis drugs (AT), for this purpose, it handles some mutations in the main genes and creates new patterns for inhibited genes. Method and materials: Researchers have their best tries to safely isolate MTB from the sputum specimens of 35 patients in some hospitals in the Tehran province and detect MTB by culture on Löwenstein-Jensen (LJ) medium and microscopic examination. DNA was extracted from the established bacterial colony by enzymatic extraction method. It was amplified by the polymerase chain reaction (PCR) method, reverse hybridization, and evaluation for detection of resistance genes; generally, researchers apply GenoType MTBDRplus assay. Results: Investigations of results declare us that 21 of the isolated specimens (about 60%) have mutation in rpoB gene, which resisted to rifampicin (most prevalence), and 8 of them (about 22.8%) have mutation in katG or inhA genes which resisted to isoniazid. Also, 4 of them (about 11.4%) don't have any mutation, and 2 of them (about 5.7%) have mutation in every three genes, which makes them resistant to the two drugs mentioned above. Conclusion: Rifampicin and isoniazid are two essential AT that using in the first line of treatment. Resistance in rpoB, and katG, and inhA genes related to mentioned drugs lead to ineffective treatment.

Keywords: mycobacterium tuberculosis, tuberculosis, drug resistance, isoniazid, rifampicin

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846 The Use of Remotely Sensed Data to Extract Wetlands Area in the Cultural Park of Ahaggar, South of Algeria

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

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The cultural park of the Ahaggar, occupying a large area of Algeria, is characterized by a rich wetlands area to be preserved and managed both in time and space. The management of a large area, by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information...), 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. Remote sensing imaging data have been very useful in the last decade in very interesting applications. They can aid in several domains such as the detection and identification of diverse wetland surface targets, topographical details, and geological features... In this work, we try to extract automatically wetlands area using multispectral remotely sensed data on-board the Earth Observing 1 (EO-1) and Landsat satellite. Both are high-resolution multispectral imager with a 30 m resolution. The instrument images an interesting surface area. We have used images acquired over the several area of interesting in the National Park of Ahaggar in the south of Algeria. An Extraction Algorithm is applied on the several spectral index obtained from combination of different spectral bands to extract wetlands fraction occupation of land use. The obtained results show an accuracy to distinguish wetlands area from the other lad use themes using a fine exploitation on spectral index.

Keywords: multispectral data, EO1, landsat, wetlands, Ahaggar, Algeria

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845 Optical Design and Modeling of Micro Light-Emitting Diodes for Display Applications

Authors: Chaya B. M., C. Dhanush, Inti Sai Srikar, Akula Pavan Parvatalu, Chirag Gowda R

Abstract:

Recently, there has been a lot of interest in µ-LED technology because of its exceptional qualities, including auto emission, high visibility, low consumption of power, rapid response and longevity. Light-emitting diodes (LED) using III-nitride, such as lighting sources, visible light communication (VLC) devices, and high-power devices, are finding increasing use as miniaturization technology advances. The use of micro-LED displays in place of traditional display technologies like liquid crystal displays (LCDs) and organic light-emitting diodes (OLEDs) is one of the most prominent recent advances, which may even represent the next generation of displays. The development of fully integrated, multifunctional devices and the incorporation of extra capabilities into micro-LED displays, such as sensing, light detection, and solar cells, are the pillars of advanced technology. Due to the wide range of applications for micro-LED technology, the effectiveness and dependability of these devices in numerous harsh conditions are becoming increasingly important. Enough research has been conducted to overcome the under-effectiveness of micro-LED devices. In this paper, different Micro LED design structures are proposed in order to achieve optimized optical properties. In order to attain improved external quantum efficiency (EQE), devices' light extraction efficiency (LEE) has also been boosted.

Keywords: finite difference time domain, light out coupling efficiency, far field intensity, power density, quantum efficiency, flat panel displays

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844 Carbon Nanomaterials from Agricultural Wastes for Adsorption of Organic Pollutions

Authors: Magdalena Blachnio, Viktor Bogatyrov, Mariia Galaburda, Anna Derylo-Marczewska

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Agricultural waste materials from traditional oil mill and after extraction of natural raw materials in supercritical conditions were used for the preparation of carbon nanomaterials (activated carbons) by two various methods. Chemical activation using acetic acid and physical activation with a gaseous agent (carbon dioxide) were chosen as mild and environmentally friendly ones. The effect of influential factors: type of raw material, temperature and activation agent on the porous structure characteristics of the materials was discussed by using N₂ adsorption/desorption isotherms at 77 K. Furthermore scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) were employed to examine the physicochemical properties of the obtained sorbents. Selection of a raw material and an optimization of the conditions of the synthesis process, allowed to obtain the cheap sorbents with a targeted distribution of pores enabling effective adsorption of the model organic pollutants carried out in the multicomponent systems. Adsorption behavior (capacity and rate) of the chosen activated carbons was estimated by utilizing Crystal violet (CV), 4-chlorophenoxyacetic acid (4-CPA), 2.4-dichlorophenoxyacetic acid (2.4-D) as the adsorbates. Both rate and adsorption capacity of the organics on the sorbents evidenced that the activated carbons could be effectively used in sewage treatment plants. The mechanisms of organics adsorption were studied and correlated with activated carbons properties.

Keywords: activated carbon, adsorption equilibrium, adsorption kinetics, organics adsorption

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843 An Engineered Epidemic: Big Pharma's Role in the Opioid Crisis

Authors: Donna L. Roberts

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2019 marked 23 years since Purdue Pharma launched its flagship drug, OxyContin, that unleashed an unprecedented epidemic touching both celebrities and common citizens, metropolitan, suburbia and rural areas and all levels of socioeconomic status. From rural Appalachia to East LA individuals, families and communities have been devastated by a trajectory of addiction that often began with the legitimate prescription of a pain killer for anything from a tooth extraction to a sports injury to recovery from surgery or chronic arthritis. Far from being a serendipitous progression of events, the proliferation of this new breed of 'miracle drug' was instead a carefully crafted marketing program aimed at both the medical community and common citizens. This research represents and in-depth investigation of the evolution of the marketing, distribution and promotion of prescription opioids by pharmaceutical companies and its relationship to the propagation of the opioid crisis. Specifically, key components of Purdue Pharma’s aggressive marketing campaign, including its bonus system and sales incentives, were analyzed in the context of the sociopolitical environment that essential created the proverbial 'perfect storm' for the changing manner in which pain is treated in the U.S. The analyses of these series of events clearly indicate their role in first, the increase in prescription of opioids for non-terminal pain relief and subsequently, the incidence of related addiction, overdose, and death. Through this examination of the conditions that facilitated and maintained this drug crisis, perhaps we can begin to chart a course toward its resolution.

Keywords: addiction, opioid, opioid crisis, Purdue Pharma

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842 Broadening the Public Sphere: Examining the Role of Community Radio in Fostering Participatory Democracy in Selected Communities in Ondo State, Nigeria

Authors: John Ibanga

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Since May 1999, when Nigeria returned to uninterrupted democratic rule, there have been various attempts by successive governments at committing themselves to democratic ideals. Such efforts include a revision of communication policies after repeated calls by civil society organisations, development partners, researchers, and academics to allow not only the commencement of campus radio broadcasting but also the takeoff of community radio broadcasting. Thus, in 2015, operating licenses were granted to several communities spread across the six geopolitical zones in the country for the establishment of community radio stations culminating in the establishment of the first community radio in Nigeria on July 17, 2015. And, since citizens’ involvement in policy matters and governance is one of the tenets of participatory democracy, it becomes imperative to investigate how the emerging community radio sector in Nigeria is facilitating participatory democracy among Nigerians, even in the face of attempts by the present government to silence all dissenting voices. This study, therefore, examines how residents in Ondo State, Southwest Nigeria, are utilising programmes on Ejule Nen and Kakaaki community radio stations in Ondo State, Nigeria, to deepen participatory democracy. Much of the existing studies on the role of community radio in participatory democracy and citizens' engagement efforts miss out on Nigeria because of the delayed implementation of community radio policy in Nigeria being Africa’s most populous nation as well as a major player in the affairs of the African continent. While the participatory communication and communication infrastructure theories were used as framework, data were collected from in-depth interviews with staff of the community radio station and community leaders, focus group discussions with the community residents, and qualitative content analysis of programmes on the station. The residents used the community radio stations as platforms for demanding accountability from government, mobilising resources for the execution of a number of community projects, promoting credible electoral practices, and influencing the implementation of free education policy in their communities. Hence the community radio stations became the reliable and authoritative voices of residents for participating in the public sphere and, generally, the democratic process.

Keywords: community, community radio, democracy, participatory democracy

Procedia PDF Downloads 126
841 The Abundance and Distribution of Locally Important Species Along Different Altitude: The Case of Mountain Damota, Wolaita South Ethiopia

Authors: Tamirat Solomon, Tadesse Faltamo, Belete Limani

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This study was conducted on the mountain Damota of Wolaita to assess the abundance and spatial distribution of two locally important indigenous medicinal plants on the mountain landscape. A total of 130 plots measuring 20x20m were established along eight systematically laid transect lines. In each plot, the abundance and distribution of Hagenia abyssinica (tree) and Pentas schiperiana Vatke (shrub) were evaluated. The abundance and distribution of H. abyssinica were evaluated by measuring height and DBH for mature trees and counting seedlings and saplings, whereas the P. schiperiana Vatke was assessed for its abundance and distribution by counting in each plot. In the entire study plots, a total of 485 H. abyssinica and 760 P. schiperiana vatake were recorded. It was observed that the distribution of the species increased while the altitude increased and the highest abundance of the species was recorded at an altitude range between 2332 and 2661m.a.s.l. However, at the altitudes below 2320 m.a.s.l., the species distributions and abundance was decreased, indicating either the ecological preference of the species or the extraction of the local community surrounding the mountain influenced the species. On average, only 28 seedlings/ha of H. abyssinica and 146/ha of P. schiperiana vatke were recorded in the study areas showing the tendency of decline in the abundance and distribution of both species. Finally, we recommend management intervention for the socially important species which are under threat on the mountain landscape.

Keywords: indigenous medicinal plants, H.abyssinic, P. schiperiana, distribution, abundance, socio-economic importance

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840 Controlling RPV Embrittlement through Wet Annealing in Support of Life Extension

Authors: E. A. Krasikov

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As a main barrier against radioactivity outlet reactor pressure vessel (RPV) is a key component in terms of NPP safety. Therefore, present-day demands in RPV reliability enhance have to be met by all possible actions for RPV in-service embrittlement mitigation. Annealing treatment is known to be the effective measure to restore the RPV metal properties deteriorated by neutron irradiation. There are two approaches to annealing. The first one is so-called ‘dry’ high temperature (~475°C) annealing. It allows obtaining practically complete recovery, but requires the removal of the reactor core and internals. External heat source (furnace) is required to carry out RPV heat treatment. The alternative approach is to anneal RPV at a maximum coolant temperature which can be obtained using the reactor core or primary circuit pumps while operating within the RPV design limits. This low temperature «wet» annealing, although it cannot be expected to produce complete recovery, is more attractive from the practical point of view especially in cases when the removal of the internals is impossible. The first RPV «wet» annealing was done using nuclear heat (US Army SM-1A reactor). The second one was done by means of primary pumps heat (Belgian BR-3 reactor). As a rule, there is no recovery effect up to annealing and irradiation temperature difference of 70°C. It is known, however, that along with radiation embrittlement neutron irradiation may mitigate the radiation damage in metals. Therefore, we have tried to test the possibility to use the effect of radiation-induced ductilization in ‘wet’ annealing technology by means of nuclear heat utilization as heat and neutron irradiation sources at once. In support of the above-mentioned conception the 3-year duration reactor experiment on 15Cr3NiMoV type steel with preliminary irradiation at operating PWR at 270°C and following extra irradiation (87 h at 330°C) at IR-8 test reactor was fulfilled. In fact, embrittlement was partly suppressed up to value equivalent to 1,5 fold neutron fluence decrease. The degree of recovery in case of radiation enhanced annealing is equal to 27% whereas furnace annealing results in zero effect under existing conditions. Mechanism of the radiation-induced damage mitigation is proposed. It is hoped that «wet » annealing technology will help provide a better management of the RPV degradation as a factor affecting the lifetime of nuclear power plants which, together with associated management methods, will help facilitate safe and economic long-term operation of PWRs.

Keywords: controlling, embrittlement, radiation, steel, wet annealing

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