Search results for: lung extraction

Authors: G. R. Hashemi Tabar, G. R. Razmi, F. Mirshekar

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Echinococcus granulosus have ten strains from G1 to G9. Each strain is related to special intermediated host. The morphology, epidemiology, treatment and control in these strains are different. There are many morphological and molecular methods to differentiate of Echinococcus strains. However, using both methods were provided better information about identification of each strain. The aim of study was to identify Echinococcus granulosus strain of hydrated cysts in slaughtered sheep using morphological and molecular methods in Mashhad area. In the present study, the infected liver and lung with hydatid cysts were collected and transferred to laboratory. The hydatid cyst liquid was extracted and morphological characters of rostellar hook protosclocies were measured using micrometer ocular. The total length of large blade length of large hooks, total length of small and blade length of small hooks, and number of hooks per protoscolex were 23± 0.3μm, 11.7±0.5 μm, 19.3±1.1 μm,8±1.1 and 33.7±0.7 μm, respectively. In molecular section of the study, DNA each samples was extracted with MBST Kit and development of PCR using special primers (EgF, EgR) which amplify fragment of ITS1 gen. The PCR product was digested with Bsh1236I enzyme. Based on pattern of PCR-RLFP results (four band forming), G1, G2 and G3 strain of Echinococcus granulosus were obtained. Differentiation of three strains was done using sequencing analysis and G1 strain was diagnosed. The agreement between the molecular results with morphometric characters of rosetellar hook was confirmed the presence of G1 strain of Echinococcus in the slaughtered sheep of Mashhad area.

Keywords: Echinococcus granulosus, Hydatid cyst, PCR, sheep

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Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

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This proposal aims for semantic enrichment between glossaries using the Simple Knowledge Organization System (SKOS) vocabulary to discover synonyms, hyponyms and hyperonyms semiautomatically, in Brazilian Portuguese, generating new semantic relationships based on WordNet. To evaluate the quality of this proposed model, experiments were performed by the use of two sets containing new relations, being one generated automatically and the other manually mapped by the domain expert. The applied evaluation metrics were precision, recall, f-score, and confidence interval. The results obtained demonstrate that the applied method in the field of Oil Production and Extraction (E&P) is effective, which suggests that it can be used to improve the quality of terminological mappings. The procedure, although adding complexity in its elaboration, can be reproduced in others domains.

Keywords: ontology matching, mapping enrichment, semantic web, linked data, SKOS

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Authors: Hala Alshamlan, Ghada Badr, Yousef Alohali

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Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile.

Keywords: gene selection, feature selection, cancer classification, microarray, gene expression profile

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Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

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Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

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Authors: Yik Sin Chan, Bee Ling Chuah, Wei Quan Chan, Ri Jin Cheng, Yan Hang Oon, Kong Soo Khoo, Nam Weng Sit

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Traditionally, medicinal plants have been used to treat different kinds of ailments including infectious diseases. They serve as a good source of lead compounds for the development of new and safer anti-infective agents. This study aimed to investigate the antimicrobial potential of the leaves of three medicinal plants, namely Catunaregam spinosa (Rubiaceae; Mountain pomegranate), Houttuynia cordata (Saururaceae; "fishy-smell herb") and Rhapis excelsa (Arecaceae; “broadleaf lady palm”). The leaves extracts were obtained by sequential extraction using hexane, chloroform, ethyl acetate, ethanol, methanol and water. The antibacterial and antifungal activities were assessed using a colorimetric broth microdilution method against a panel of human pathogenic bacteria (Gram-positive: Bacillus cereus and Staphylococcus aureus; Gram-negative: Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa) and fungi (yeasts: Candida albicans, Candida parapsilosis and Cryptococcus neoformans; Moulds: Aspergillus fumigatus and Trichophyton mentagrophytes) respectively; while antiviral activity was evaluated against the Chikungunya virus on monkey kidney epithelial (Vero) cells by neutral red uptake assay. All the plant extracts showed bacteriostatic activity, however, only 72% of the extracts (13/18) were found to have bactericidal activity. The lowest minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were given by the hexane extract of C. spinosa against S. aureus with the values of 0.16 and 0.31 mg/mL respectively. All the extracts also possessed fungistatic activity. Only the hexane, chloroform and ethyl acetate extracts of H. cordata exerted inhibitory activity against A. fumigatus, giving the lowest fungal susceptibility index of 16.7%. In contrast, only 61% of the extracts (11/18) showed fungicidal activity. The ethanol extract of R. excelsa exhibited the strongest fungicidal activity against C. albicans, C. parapsilosis and T. mentagrophytes with minimum fungicidal concentration (MFC) values of 0.04–0.08 mg/mL, in addition to its methanol extract against T. mentagrophytes (MFC=0.02 mg/mL). For anti-Chikungunya virus activity, only chloroform and ethyl acetate extracts of R. excelsa showed significant antiviral activity with 50% effective concentrations (EC50) of 29.9 and 78.1 g/mL respectively. Extracts of R. excelsa warrant further investigations into their active principles responsible for antifungal and antiviral properties.

Keywords: bactericidal, Chikungunya virus, extraction, fungicidal

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Authors: Mekha Mathew, Varun P Gopi

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Wireless Capsule Endoscopy (WCE) has become a great device in Gastrointestinal (GI) tract diagnosis, which can examine the entire GI tract, especially the small intestine without invasiveness and sedation. Bleeding in the digestive tract is a symptom of a disease rather than a disease itself. Hence the detection of bleeding is important in diagnosing many diseases. In this paper we proposes a novel method for distinguishing bleeding regions from normal regions based on Contourlet transform and Local Binary Pattern (LBP). Experiments show that this method provides a high accuracy rate of 96.38% in CIE XYZ colour space for k-Nearest Neighbour (k-NN) classifier.

Keywords: Wireless Capsule Endoscopy, local binary pattern, k-NN classifier, contourlet transform

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Authors: Samar Rabah

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Background: Incense woods are special kind of trees called Agarwood, which characterized by good smelling odors and many medical benefits. Incense smoke is heavily used in Saudi Arabia although comprehensive studies of its effects on health are limited. The present study demonstrated lung ultrastructure changes of mice after exposure and cessation to Incense smoke. Eighty mice are divided equally into four groups, three groups are exposed to different concentrations of Incense smoke (2, 4 and 6 gm) for three months, while the fourth group is control one. At the end of each month, lungs of five animals from each group are gathered, while the last five animals from each group are kept for another 60 days without exposure to the Incense smoke to allow for recovery. Results: Transmission electron microscope investigations of all exposed groups showed hypertrophy and hyperplasia in Clara Cells and some an enlargement of the macrophage to the point that it fills a large part of the alveolar lumen. Scanning electron microscope marks presence of mucus materials attached to the epithelial bronchioles. After prevention of exposure to the Incense smoke for 60 days, necrosis and degeneration in some cells of epithelial bronchioles, fibrosis of peribronchial, thickening in alveolar walls and aggregation of lymphoid cells were demonstrated. Conclusion: Based on the above findings and other related studies (not published), we conclude that exposure to Incense smoke causes harmful effects due to sever changes in pulmonary ultrastructure, such effects do not disappear even when Incense smoke inhalation was stopped. Therefore, we recommend that Incense smoke should use only in open places to reduce its harms.

Keywords: Incense smoke, lungs, ultrastructure of lungs, Agarwood

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Authors: Vibha Devi, Shabina Khanam

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Hemp (Cannabis sativa) possesses a rich content of ω-6 linoleic and ω-3 linolenic essential fatty acid in the ratio of 3:1, which is a rare and most desired ratio that enhances the quality of hemp oil. These components are beneficial for the development of cell and body growth, strengthen the immune system, possess anti-inflammatory action, lowering the risk of heart problem owing to its anti-clotting property and a remedy for arthritis and various disorders. The present study employs supercritical fluid extraction (SFE) approach on hemp seed at various conditions of parameters; temperature (40 - 80) °C, pressure (200 - 350) bar, flow rate (5 - 15) g/min, particle size (0.430 - 1.015) mm and amount of co-solvent (0 - 10) % of solvent flow rate through central composite design (CCD). CCD suggested 32 sets of experiments, which was carried out. As SFE process includes large number of variables, the present study recommends the application of resampling techniques for cross-validation of the obtained data. Cross-validation refits the model on each data to achieve the information regarding the error, variability, deviation etc. Bootstrap and jackknife are the most popular resampling techniques, which create a large number of data through resampling from the original dataset and analyze these data to check the validity of the obtained data. Jackknife resampling is based on the eliminating one observation from the original sample of size N without replacement. For jackknife resampling, the sample size is 31 (eliminating one observation), which is repeated by 32 times. Bootstrap is the frequently used statistical approach for estimating the sampling distribution of an estimator by resampling with replacement from the original sample. For bootstrap resampling, the sample size is 32, which was repeated by 100 times. Estimands for these resampling techniques are considered as mean, standard deviation, variation coefficient and standard error of the mean. For ω-6 linoleic acid concentration, mean value was approx. 58.5 for both resampling methods, which is the average (central value) of the sample mean of all data points. Similarly, for ω-3 linoleic acid concentration, mean was observed as 22.5 through both resampling. Variance exhibits the spread out of the data from its mean. Greater value of variance exhibits the large range of output data, which is 18 for ω-6 linoleic acid (ranging from 48.85 to 63.66 %) and 6 for ω-3 linoleic acid (ranging from 16.71 to 26.2 %). Further, low value of standard deviation (approx. 1 %), low standard error of the mean (< 0.8) and low variance coefficient (< 0.2) reflect the accuracy of the sample for prediction. All the estimator value of variance coefficients, standard deviation and standard error of the mean are found within the 95 % of confidence interval.

Keywords: resampling, supercritical fluid extraction, hemp oil, cross-validation

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Authors: Zoi Konsoula

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The increasing prevalence of Alzheimer’s disease (AD) and diabetes mellitus (DM) constitutes them major global health problems. Recently, the inhibition of key enzyme activity is considered a potential treatment of both diseases. Specifically, inhibition of acetylcholinesterase (AChE), the key enzyme involved in the breakdown of the neurotransmitter acetylcholine, is a promising approach for the treatment of AD, while inhibition of α-amylase retards the hydrolysis of carbohydrates and, thus, reduces hyperglycemia. Unfortunately, commercially available AChE and α-amylase inhibitors are reported to possess side effects. Consequently, there is a need to develop safe and effective treatments for both diseases. In the present study, pomegranate peel (PP) was extracted using various solvents of increasing polarity, while two extraction methods were employed, the conventional maceration and the ultrasound assisted extraction (UAE). The concentration of bioactive phytoconstituents, such as total phenolics (TPC) and total flavonoids (TFC) in the prepared extracts was evaluated by the Folin-Ciocalteu and the aluminum-flavonoid complex method, respectively. Furthermore, the anti-neurodegenerative and anti-hyperglycemic activity of all extracts was determined using AChE and α-amylase inhibitory activity assays, respectively. The inhibitory activity of the extracts against AChE and α-amylase was characterized by estimating their IC₅₀ value using a dose-response curve, while galanthamine and acarbose were used as positive controls, respectively. Finally, the kinetics of AChE and α-amylase in the presence of the most inhibitory potent extracts was determined by the Lineweaver-Burk plot. The methanolic extract prepared using the UAE contained the highest amount of phytoconstituents, followed by the respective ethanolic extract. All extracts inhibited acetylcholinesterase in a dose-dependent manner, while the increased anticholinesterase activity of the methanolic (IC₅₀ = 32 μg/mL) and ethanolic (IC₅₀ = 42 μg/mL) extract was positively correlated with their TPC content. Furthermore, the activity of the aforementioned extracts was comparable to galanthamine. Similar results were obtained in the case of α-amylase, however, all extracts showed lower inhibitory effect on the carbohydrate hydrolyzing enzyme than on AChE, since the IC₅₀ value ranged from 84 to 100 μg/mL. Also, the α-amylase inhibitory effect of the extracts was lower than acarbose. Finally, the methanolic and ethanolic extracts prepared by UAE inhibited both enzymes in a mixed (competitive/noncompetitive) manner since the Kₘ value of both enzymes increased in the presence of extracts, while the Vmax value decreased. The results of the present study indicate that PP may be a useful source of active compounds for the management of AD and DM. Moreover, taking into consideration that PP is an agro-industrial waste product, its valorization could not only result in economic efficiency but also reduce the environmental pollution.

Keywords: acetylcholinesterase, Alzheimer’s disease, α-amylase, diabetes mellitus, pomegranate

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Authors: Olga Kononova, Sergey Lyapin

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Global information society requirements are transparency and reliability of data, as well as ability to manage information resources independently; particularly to search, to analyze, to evaluate information, thereby obtaining new expertise. Moreover, it is satisfying the society information needs that increases the efficiency of the enterprise management and public administration. The study of structurally organized thematic and semantic contexts of different types, automatically extracted from unstructured data, is one of the important tasks for the application of information technologies in education, science, culture, governance and business. The objectives of this study are the contextual knowledge typologization, selection or creation of effective tools for extracting and analyzing contextual knowledge. Explication of various kinds and forms of the contextual knowledge involves the development and use full-text search information systems. For the implementation purposes, the authors use an e-library 'Humanitariana' services such as the contextual search, different types of queries (paragraph-oriented query, frequency-ranked query), automatic extraction of knowledge from the scientific texts. The multifunctional e-library «Humanitariana» is realized in the Internet-architecture in WWS-configuration (Web-browser / Web-server / SQL-server). Advantage of use 'Humanitariana' is in the possibility of combining the resources of several organizations. Scholars and research groups may work in a local network mode and in distributed IT environments with ability to appeal to resources of any participating organizations servers. Paper discusses some specific cases of the contextual knowledge explication with the use of the e-library services and focuses on possibilities of new types of the contextual knowledge. Experimental research base are science texts about 'e-government' and 'computer games'. An analysis of the subject-themed texts trends allowed to propose the content analysis methodology, that combines a full-text search with automatic construction of 'terminogramma' and expert analysis of the selected contexts. 'Terminogramma' is made out as a table that contains a column with a frequency-ranked list of words (nouns), as well as columns with an indication of the absolute frequency (number) and the relative frequency of occurrence of the word (in %% ppm). The analysis of 'e-government' materials showed, that the state takes a dominant position in the processes of the electronic interaction between the authorities and society in modern Russia. The media credited the main role in these processes to the government, which provided public services through specialized portals. Factor analysis revealed two factors statistically describing the used terms: human interaction (the user) and the state (government, processes organizer); interaction management (public officer, processes performer) and technology (infrastructure). Isolation of these factors will lead to changes in the model of electronic interaction between government and society. In this study, the dominant social problems and the prevalence of different categories of subjects of computer gaming in science papers from 2005 to 2015 were identified. Therefore, there is an evident identification of several types of contextual knowledge: micro context; macro context; dynamic context; thematic collection of queries (interactive contextual knowledge expanding a composition of e-library information resources); multimodal context (functional integration of iconographic and full-text resources through hybrid quasi-semantic algorithm of search). Further studies can be pursued both in terms of expanding the resource base on which they are held, and in terms of the development of appropriate tools.

Keywords: contextual knowledge, contextual search, e-library services, frequency-ranked query, paragraph-oriented query, technologies of the contextual knowledge extraction

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Authors: Sajjad Rezaei, Mahdieh Molanouri Shamsi, Azadeh Jamali

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Background and purpose: Surfactant protein D (SP-D) is a lung-specific protein that is detectable in human plasma. Effect of exercise training on SP-D levels as well as its relation to metabolic indices is not known. The present study then aimed to investigate the effects of 10 weeks of aerobic training on serum levels of SP-D and insulin resistance in women with type 2 diabetes. Materials and methods: Twenty-two overweight women with type 2 diabetes mellitus were recruited through deliberate sampling and randomly assigned to intervention and control groups (11 in each group). The intervention group underwent a progressive aerobic training program for 10 weeks, 3 days per week, 30-55 min/day at 50-75% heart rate reserve (HRR). Control group continued with its everyday routine. Blood samples were obtained before and after training for biochemical analysis. Within-group and between-group differences were analyzed with paired and independent t-tests in spss software, respectively, and the relation between variables was analyzed with Pearson’s correlation coefficient (all at P = 0.05). Results: Significant differences were observed between groups in leptin, glucose, waist circumference and VO2 max after training. SP-D was decreased and VO2 max was increased significantly in intervention group. However, no significant correlation was observed between SP-D and other variables. Conclusion: Since there was no corresponding decrease in insulin resistance with decreased levels of SP-D, it seems unlikely for SP-D to mediate the association between obesity and insulin resistance in type 2 diabetics.

Keywords: exercise training, SP-D, insulin resistance, type 2 diabetes

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Authors: Mounir Baccar, Imen Jmal

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Because of the rise in energy costs, thermal storage systems designed for the heating and cooling of buildings are becoming increasingly important. Energy storage can not only reduce the time or rate mismatch between energy supply and demand but also plays an important role in energy conservation. One of the most preferable storage techniques is the Latent Heat Thermal Energy Storage (LHTES) by Phase Change Materials (PCM) due to its important energy storage density and isothermal storage process. This paper presents a numerical study of the solidification of a PCM (paraffin RT27) in a rectangular thermal storage exchanger for air conditioning systems taking into account the presence of natural convection. Resolution of continuity, momentum and thermal energy equations are treated by the finite volume method. The main objective of this numerical approach is to study the effect of natural convection on the PCM solidification time and the impact of fins number on heat transfer enhancement. It also aims at investigating the temporal evolution of PCM solidification, as well as the longitudinal profiles of the HTF circling in the duct. The present research undertakes the study of two cases: the first one treats the solidification of PCM in a PCM-air heat exchanger without fins, while the second focuses on the solidification of PCM in a heat exchanger of the same type with the addition of fins (3 fins, 5 fins, and 9 fins). Without fins, the stratification of the PCM from colder to hotter during the heat transfer process has been noted. This behavior prevents the formation of thermo-convective cells in PCM area and then makes transferring almost conductive. In the presence of fins, energy extraction from PCM to airflow occurs at a faster rate, which contributes to the reduction of the discharging time and the increase of the outlet air temperature (HTF). However, for a great number of fins (9 fins), the enhancement of the solidification process is not significant because of the effect of confinement of PCM liquid spaces for the development of thermo-convective flow. Hence, it can be concluded that the effect of natural convection is not very significant for a high number of fins. In the optimum case, using 3 fins, the increasing temperature of the HTF exceeds approximately 10°C during the first 30 minutes. When solidification progresses from the surfaces of the PCM-container and propagates to the central liquid phase, an insulating layer will be created in the vicinity of the container surfaces and the fins, causing a low heat exchange rate between PCM and air. As the solid PCM layer gets thicker, a progressive regression of the field of movements is induced in the liquid phase, thus leading to the inhibition of heat extraction process. After about 2 hours, 68% of the PCM became solid, and heat transfer was almost dominated by conduction mechanism.

Keywords: heat transfer enhancement, front solidification, PCM, natural convection

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Authors: Pratibha, Jyoti Kori

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Particles in industry, harvesting, coal mines, etc. may not necessarily be spherical in shape. In general, it is difficult to find perfectly spherical particle. The prediction of movement and deposition of non spherical particle in distinct airway generation is much more difficult as compared to spherical particles. Moreover, there is extensive inflexibility in deposition between ducts of a particular generation and inside every alveolar duct since particle concentrations can be much bigger than the mean acinar concentration. Consequently, a large number of particles fail to be exhaled during expiration. This study presents a mathematical model for the movement and deposition of those non-spherical particles by using particle aspect ratio and shape factor. We analyse the pulsatile behavior underneath sinusoidal wall oscillation due to periodic breathing condition through a non-Darcian porous medium or inside pulmonary region. Since the fluid is viscous and Newtonian, the generalized Navier-Stokes equation in two-dimensional coordinate system (r, z) is used with boundary-layer theory. Results are obtained for various values of Reynolds number, Womersley number, Forchsheimer number, particle aspect ratio and shape factor. Numerical computation is done by using finite difference scheme for very fine mesh in MATLAB. It is found that the overall air velocity is significantly increased by changes in aerodynamic diameter, aspect ratio, alveoli size, Reynolds number and the pulse rate; while velocity is decreased by increasing Forchheimer number.

Keywords: deposition, interstitial lung diseases, non-Darcian medium, numerical simulation, shape factor

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Authors: Y. Xu, L. Xiong, Z. Xu

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In order to protect data privacy, image with sensitive or private information needs to be encrypted before being outsourced to the cloud. However, this causes difficulties in image retrieval and data management. A secure image retrieval method based on orthogonal decomposition is proposed in the paper. The image is divided into two different components, for which encryption and feature extraction are executed separately. As a result, cloud server can extract features from an encrypted image directly and compare them with the features of the queried images, so that the user can thus obtain the image. Different from other methods, the proposed method has no special requirements to encryption algorithms. Experimental results prove that the proposed method can achieve better security and better retrieval precision.

Keywords: secure image retrieval, secure search, orthogonal decomposition, secure cloud computing

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Authors: Natalia Efremova, Sergey Tarasenko

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We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

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Authors: Thiago M. R. Dias, Patrícia M. Dias, Gray F. Moita

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The production and publication of scientific works have increased significantly in the last years, being the Internet the main factor of access and distribution of these works. Faced with this, there is a growing interest in understanding how scientific research has evolved, in order to explore this knowledge to encourage research groups to become more productive. Therefore, the objective of this work is to explore repositories containing data from scientific publications and to characterize keyword networks of these publications, in order to identify the most relevant keywords, and to highlight those that have the greatest impact on the network. To do this, each article in the study repository has its keywords extracted and in this way the network is  characterized, after which several metrics for social network analysis are applied for the identification of the highlighted keywords.

Keywords: bibliometrics, data analysis, extraction and data integration, scientometrics

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Authors: Amna Beshir Medani Ahmed, Samia Mohammed Ali El Badwi, Ahmed El Amin Mohammed

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This work has been managed to yield toxicity information on water treatment agents in the Sudan namely polyDADMAC, using New Zealand rabbits at multiple daily oral doses for a period of 10 weeks. Thirty-three heads of New Zealand rabbits were divided into 11 groups, each of three. Group 1 animals were the undosed controls. Test groups of either species were given polyDADMAC at similar dose rates of 0.5, 2.5, 4.5, 10, 15, 20, 25, 50, 100 and 150 mg/kg body weight respectively for groups 2,3,4,5,6,7,8,9,10 and 11. Clinical signs were closely observed with postmortem and histopathological examinations. Chemical investigations included enzymatic concentrations of ALP, GOT, CK, GPT and LDH together with hematological changes in Hb, PCV, RBCs and WBCs. Mortalities occurred to variable degrees irrespective of the dose level. On polyDADMAC challenge, the test species showed clinical signs of dullness, loss of weight, anorexia, diarrhea, difficulty in respiration, hind limb paralysis and recumbency. Notably oral dosing with polyDADMAC caused lung emphysema, hepatic and renal dysfunctions, irregularity in enzymatic activities and serum metabolites, sloughing of intestinal epithelium, decreased electrolytes in serum, and splenic haemosiderosis. On evaluation of the above results, polyDADMAC was considered toxic to New Zealand rabbits at all dose rates tried. Practical implications of the results were highlighted and suggestions for future work were put forward.

Keywords: polydiallyldiethylaluminiumchloride (polyDADMAC), nubian goats, toxicity of drinking water, treatment of drinking water using chemicals

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Authors: Hsin-Chih Lai, Yung-Lung Lee, Yun-Yao Chi, Ching-Yi Horng, Pei-Chih Wu, Hsien-Chang Wang

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Taiwan, a climatically challenged island, has always been keen on the issue of water resource management due to its limitations in water storage. Since water resource management has been the focal point of many adaptations to climate change, there has been a lack of attention on another issue, water quality. This study chooses the Errer River Basin as the experimental focus for water quality in Taiwan. With the Errer River Basin being one of the most polluted rivers in Taiwan, this study observes the effects of climate change on this river over a period of time. Taiwan is also targeted by multiple typhoons every year, the heavy rainfall and strong winds create problems of pollution being carried to different river segments, including into the ocean. This study aims to create an impact and risk assessment on Errer River Basin, to show the connection from climate change to potential extreme events, which in turn could influence water quality and ultimately human health. Using dynamic downscaling, this study narrows the information from a global scale to a resolution of 1 km x 1 km. Then, through interpolation, the resolution is further narrowed into a resolution of 200m x 200m, to analyze the past, present, and future of extreme events. According to different climate change scenarios, this study designs an assessment index on the vulnerability of the Errer River Basin. Through this index, Errer River inhabitants can access advice on adaptations to climate change and act accordingly.

Keywords: climate change, adaptation, water quality, risk assessment

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Manal Al Bahri, Saif Al Mubahisi, Shamsa Al Shahaimi, Asma Al Qasabi, Jamal Al Aghbari

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Introduction: ILD is a common disease worldwide and in Oman. No previous Omani study was published regarding ILD prognosis based on baseline PFT results and other factors. This study aims to determine the severity of ILD by the baseline PFT, correlate between baseline PFT and outcome, and study other factors that influence disease mortality. Method: It is a retrospective cohort study; data was collected from January 2011 to December 2021 from electronic patient records (EPR). Means, Standard Deviations, frequencies, and Chi-square tests were used to examine the different variables in the study. Results: The total population of the study was 146 patients; 87 (59.6%) were females, and 59 (40.4%) were males. The median age was 59 years. Age at diagnosis, CVA, rheumatological disease, and baseline FVC were found to be statistically significant predictors of mortality .59.6% of the patients are diagnosed with IPF. Most of our study patients had mild disease based on baseline FVC. Death was higher with the more severe disease based on FVC. In mild disease (FVC >70%), 26.9% of the patients died. In moderate disease (FVC 50-69%),55.7% of the patients died, and in the severe group (FVC <50 %), 55.1% died. This was statistically significant with a P value of 0. 001. There is no statistically significant difference in the overall survival distribution between the different groups of DLCO. Conclusion: In our study, we found that ILD is more common among females, but death is more common among males. Based on baseline PFT, we can predict mortality by FVC level, as moderate to severe limitation is associated with a lower survival rate. DLCO was not a statistically significant parameter associated with mortality.

Keywords: PFT, ILD, FVC, DLCO, mortality

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Authors: Muslim Khan, Kenneth B. Jensen, Kevin A. Francesconi

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Trace amounts (ca 1 µg/L, 13 nM) of arsenic are present in sea water mostly as the oxyanion arsenate. In contrast, arsenic is present in marine biota (animals and algae) at very high levels (up to100,000 µg/kg) a significant portion of which is present as lipid-soluble compounds collectively termed arsenolipids. The complex nature of sea water presents an analytical challenge to detect trace compounds and monitor their environmental path. We developed a simple method using liquid-liquid extraction combined with HPLC-High Resolution Mass Spectrometer capable of detecting trace of arsenolipids (99 % of the sample matrix while recovering > 80 % of the six target arsenolipids with limit of detection of 0.003 µg/L.)

Keywords: arsenolipids, sea water, HPLC-high resolution mass spectrometry

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Authors: A. N. Paithane, D. S. Bormane, S. D. Shirbahadurkar

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It has been seen that emotion recognition is an important research topic in the field of Human and computer interface. A novel technique for Feature Extraction (FE) has been presented here, further a new method has been used for human emotion recognition which is based on HHT method. This method is feasible for analyzing the nonlinear and non-stationary signals. Each signal has been decomposed into the IMF using the EMD. These functions are used to extract the features using fission and fusion process. The decomposition technique which we adopt is a new technique for adaptively decomposing signals. In this perspective, we have reported here potential usefulness of EMD based techniques.We evaluated the algorithm on Augsburg University Database; the manually annotated database.

Keywords: intrinsic mode function (IMF), Hilbert-Huang transform (HHT), empirical mode decomposition (EMD), emotion detection, electrocardiogram (ECG)

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Authors: Tudor Barbu

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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Document Analysis is an important research field that aims to gather the information by analyzing the data in documents. As one of the important targets for many fields is to understand what people actually want, sentimental analysis field has been one of the vital fields that are tightly related to the document analysis. This research focuses on analyzing text documents to classify each document according to its opinion. The aim of this research is to detect the emotions from text documents based on enriching the lexicon with adapting their content based on semantic patterns extraction. The proposed approach has been presented, and different experiments are applied by different perspectives to reveal the positive impact of the proposed approach on the classification results.

Keywords: document analysis, sentimental analysis, emotion detection, WEKA tool, NRC lexicon

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Authors: Kalpana Rajouriya, Ajay Taneja

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Particulates are ubiquitous in the air environment and cause serious threats to human beings, such as lung cancer, COPD, and Asthma. Particulates mainly arise from industrial effluent, vehicular emission, and other anthropogenic activities. In the glass industrial city Firozabad, real-time monitoring of size segregated Particulate Matter (PM) and black carbon was done by Aerosol Black Carbon Detector (ABCD) and GRIMM portable aerosol Spectrometer at two different sites in which one site is urban and another is rural. The average mass concentration of size segregated PM during the study period (March & April 2022) was recorded as PM10 (223.73 g/m⁻³), PM5.0 (44.955 g/m⁻³), PM2.5 (59.275 g/m⁻³), PM1.0 (33.02 g/m⁻³), PM0.5 (2.05 g/m⁻³), and PM0.25 (2.99 g/m⁻³). The highest concentration of BC was found in Urban due to the emissions from diesel engines and wood burning, while NO2 was highest at the rural sites. The average concentrations of PM10 (6.08 and 2.73 times) PM2.5 exceeded the NAAQS and WHO guidelines. Particulate Matter deposition and health risk assessment was done by MPPD and USEPA model to know about the particulate matter toxicity in industrial residents. Health risk assessment results showed that Children are most likely to be affected by exposure of PM10 and PM2.5 and may have various non-carcinogenic and carcinogenic diseases. Deposition results inferred that the sensitive exposed population, especially 9 years old children, have high PM deposition as well as visualization and may be at risk of developing health-related problems from exposure to size-segregated PM. They will be discussed during presentation.

Keywords: particulate matter, black carbon, NO2, deposition of PM, health risk

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Authors: O. M. M. Sabry, Abeer M. El Sayed

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The essential oils from the aerial parts and flowers of Haplophyllum tuberculatum (Forsskal) Adr. Juss (Rutaceae) growing in Libya were obtained separately by hydro-distillation using a Clevenger-type apparatus. The essential oils yield were (0.4, 1.5w/w%) respectively based on the dry weight of the plant. The oils were analyzed by GC-MS. Twenty four constituents, amounting to 96.6%, were identified in the oil of the aerial parts. The predominant compounds were among the non oxygenated terpenoids (82.4%) as monoterpene hydrocarbons, represented by sabinen (26.4 %), δ-terpinen (26 %), β-phellandrene (10.4%) and 3-carene (3.86%). Zingiberine (0.4%) and β-sesquiphellandrene (0.12%) were the major sesquiterpene hydrocarbons identified. Oxygenated monoterpenes were represented by eucalyptol (5.5%) and piperitone (5.55%). Twenty six constituents, equivalent to 99.5%, were identified in the oil of the flowers. The dominance of monoterpene hydrocarbons in the flowers oil can be attributed to the high percentage of γ-terpinen (38.44%), β-phellandrene (10.0%), α- phellandrene (2.33%), 3,4-dimethyl-1,5-cyclooctadiene (6.67%), β-myrecene (6.04%), 3-carene (5.43%) and α-pinene (1.3%).While the oxygenated monoterpenes can be contributed to the trans-piperitol (4.67%) and piperitone (2.07%). Sesquiterpene hydrocarbons were not identified in the oil of the flower of H. tuberculatum. Variation in constitution between oils of Libyan H. tuberculatum and that obtained from other countries can be due to both environmental and genetic factors. The essential oils have demonstrated variable antimicrobial activities against certain micro-organisms. Also have revealed marked in vitro cytotoxicity against lung (H1299), liver (HEPG2) carcinoma cell line and variably effective as anti-inflammatory and antioxidant.

Keywords: Halpophyllum tuberculatum, rutaceae, essential oil, antimicrobial, anti-inflammatory, antitumor, antioxidant, Libya

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Authors: S. Vasailor, C. Rattanakawin

Abstract:

Electro-winning of copper metal from dilute sulfate solution (13.7 g/L) was performed in a lab electrolytic cell with stainless-steel cathode and lead-alloy anode. The effects of various parameters including cell voltage, electro-winning temperature and time were studied in order to acquire an appropriate current efficiency of copper deposition. The highest efficiency is about 95% obtaining from electro-winning condition of 3V, 55°C and 3,600 s correspondingly. The cathode copper with 95.5% Cu analyzed using atomic absorption spectrometry can be obtained from this single-winning condition. In order to increase the copper grade, solvent extraction should be used to increase the sulfate concentration, say 50 g/L, prior to winning the cathode copper effectively.

Keywords: copper metal, current efficiency, dilute sulfate solution, electro-winning

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Authors: A. Ameur Ameur, H. Boukherrouba

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In red meat slaughterhouses a significant number of organs and carcasses were seized because of the presence of lesions of various origins. The objective of this study is to characterize and evaluate the frequency of these lesions in the slaughterhouse of the Wilaya of BOUIRA. On cattle slaughtered in 2646 and inspected 72% of these carcasses have been no seizures against 28% who have undergone at least one entry. 325 lung (44%), 164 livers (22%), 149 hearts (21%) are the main saisis.38 kidneys members (5%), 33 breasts (4%) and 16 whole carcasses (2%) are less seizures parties. The main reasons are the input hydatid cyst for most seized organs such as the lungs (64.5%), livers (51.8%), hearts (23.2%), hydronephrosis for the kidneys (39.4%), and chronic mastitis (54%) for the breasts. Then we recorded second-degree pneumonia (16%) to the lungs, chronic fascioliasis (25%) for livers. A significant difference was observed (p < 0.0001) by sex, race, origin and age of all cattle having been saisie.une a specific input patterns and So pathology was recorded based on race. The local breed presented (75.2%) of hydatid cyst, (95%) and chronic fascioliasis (60%) pyelonephritis, for against the improved breed presented the entire respiratory lesions include pneumonia (64%) the chronic tuberculosis (64%) and mastitis (76%). These results are an important step in the implementation of the concept of risk assessment as the scientific basis of food legislation, by the identification and characterization of macroscopic damage leading withdrawals in meat and to establish the level of inclusion of these injuries within the recommended risk assessment systems (HACCP).

Keywords: slaughterhouses, meat safety, seizure patterns, HACCP

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Authors: Jiashu Shen

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Objectives: Spirometry is a basic reference for health evaluation which is widely used in clinical. Previous reference of spirometry is not applicable because of drastic changes of social and natural circumstance in China. A new reference values for the spirometry of the Chinese population is extremely needed. Method: Spirometric reference value was established using the statistical modeling method Generalized Additive Models for Location, Scale and Shape for forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, and maximal mid-expiratory flow (MMEF). Results: Data from 236,606 healthy non-smokers aged 4–90 years was collected from the MJ Health Check database. Spirometry equations for FEV1, FVC, MMEF, and FEV1/FVC were established, including the predicted values and lower limits of normal (LLNs) by sex. The predictive equations that were developed for the spirometric results elaborated the relationship between spirometry and age, and they eliminated the effects of height as a variable. Most previous predictive equations for Chinese spirometry were significantly overestimated (to be exact, with mean differences of 22.21% in FEV1 and 31.39% in FVC for males, along with differences of 26.93% in FEV1 and 35.76% in FVC for females) or underestimated (with mean differences of -5.81% in MMEF and -14.56% in FEV1/FVC for males, along with a difference of -14.54% in FEV1/FVC for females) the results of lung function measurements as found in this study. Through cross-validation, our equations were established as having good fit, and the means of the measured value and the estimated value were compared, with good results. Conclusions: Our study updates the spirometric reference equations for Chinese people of all ages and provides comprehensive values for both physical examination and clinical diagnosis.

Keywords: Chinese, GAMLSS model, reference values, spirometry

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Authors: Avishkar Gawade, Omkar Bansode, Ketan Bhambure, Bhargav Deore

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In recent year wide range of business intelligence technology have been applied to different area in order to support decision making process BI enables extraction of knowledge from data store. BI tools usually used in public health field for financial and administrative purposes.BI uses a dashboard in presentation stage to deliver information to information to end users.In this paper,we intend to analyze some open source BI tools on the market and their applicability in the clinical sphere taking into consideration the general characteristics of the clinical environment.A pervasive BI platform was developed using a real case in order to prove the tool viability.Analysis of various BI Tools in done with the help of several parameters such as data security,data integration,data quality reporting and anlaytics,performance,scalability and cost effectivesness.

Keywords: CDSS, EHR, business intelliegence, tools

Procedia PDF Downloads 135