Search results for: text extraction

Authors: Fuchun Li, Hong Xiao

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We propose a new early warning model for predicting financial stress events for a given future time. In this model, we examine whether credit conditions play an important role as a nonlinear propagator of shocks when predicting the likelihood of occurrence of financial stress events for a given future time. This propagation takes the form of a threshold regression in which a regime change occurs if credit conditions cross a critical threshold. Given the new early warning model for financial stress events, we evaluate the performance of this model and currently available alternatives, such as the model from signal extraction approach, and linear regression model. In-sample forecasting results indicate that the three types of models are useful tools for predicting financial stress events while none of them outperforms others across all criteria considered. The out-of-sample forecasting results suggest that the credit-regime switching model performs better than the two others across all criteria and all forecasting horizons considered.

Keywords: cut-off probability, early warning model, financial crisis, financial stress, regime-switching model, forecasting horizons

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Authors: Hamidreza Bagheri, Alireza Shariati

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There are many difficulties in the purification of raw components and products. However, researchers are seeking better ways for purification. One of the recent methods is extraction using supercritical fluids. In this study, the phase equilibria of benzoic acid-supercritical carbon dioxide system were investigated. Regarding the phase equilibria of this system, the modeling of solid-supercritical fluid behavior was performed using the Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) and Peng-Robinson equations of state (PR EoS). For this purpose, five PC-SAFT EoS parameters for pure benzoic acid were obtained using its experimental vapor pressure. Benzoic acid has association sites and the behavior of the benzoic acid-supercritical fluid system was well-predicted using both equations of state, while the binary interaction parameter values for PR EoS were negative. Genetic algorithm, which is one of the most accurate global optimization algorithms, was also used to optimize the pure benzoic acid parameters and the binary interaction parameters. The AAD% value for the PC-SAFT EoS, were 0.22 for the carbon dioxide-benzoic acid system.

Keywords: supercritical fluids, solubility, solid, PC-SAFT EoS, genetic algorithm

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Authors: Yousif Mohamed Y. Abdallah, Razan Manofely, Rajab M. Ben Yousef

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X-Ray images are very popular as a first tool for diagnosis. Automating the process of analysis of such images is important in order to help physician procedures. In this practice, teeth segmentation from the radiographic images and feature extraction are essential steps. The main objective of this study was to study correction preprocessing of x-rays images using local adaptive filters in order to evaluate contrast enhancement pattern in different x-rays images such as grey color and to evaluate the usage of new nonlinear approach for contrast enhancement of soft tissues in x-rays images. The data analyzed by using MatLab program to enhance the contrast within the soft tissues, the gray levels in both enhanced and unenhanced images and noise variance. The main techniques of enhancement used in this study were contrast enhancement filtering and deblurring images using the blind deconvolution algorithm. In this paper, prominent constraints are firstly preservation of image's overall look; secondly, preservation of the diagnostic content in the image and thirdly detection of small low contrast details in diagnostic content of the image.

Keywords: enhancement, x-rays, pixel intensity values, MatLab

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Authors: Chandra Mukherjee

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The present paper is a representation of the work done in the field of ECG signal analysis using MATLAB 7.1 Platform. An accurate and simple ECG feature extraction algorithm is presented in this paper and developed algorithm is validated using BIOPAC software. To detect the QRS peak, ECG signal is processed by following mentioned stages- First Derivative, Second Derivative and then squaring of that second derivative. Efficiency of developed algorithm is tested on ECG samples from different database and real time ECG signals acquired using BIOPAC system. Firstly we have lead wise specified threshold value the samples above that value is marked and in the original signal, where these marked samples face change of slope are spotted as R-peak. On the left and right side of the R-peak, faces change of slope identified as Q and S peak, respectively. Now the inbuilt Detection algorithm of BIOPAC software is performed on same output sample and both outputs are compared. ECG baseline modulation correction is done after detecting characteristics points. The efficiency of the algorithm is tested using some validation parameters like Sensitivity, Positive Predictivity and we got satisfied value of these parameters.

Keywords: first derivative, variable threshold, slope reversal, baseline modulation correction

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Authors: Masoud Alipanah, Sekineh Akbari, Gholamreza Dashab

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Myostatin genes or factor 8 affecting on growth and making differentiation works (GDF8) as a moderator in the development of skeletal muscle inhibitor. If mutations occurs in the coding region of myostatin, alter its inhibitory role and the muscle growth is increased. In this study, blood samples were collected randomly from 60 Kurdish sheep in northern Khorasan and DNA extraction was performed using a modified salt. A fragment 337 bp from exon 3 myostatin gene and-specific primers by using a polymerase chain reaction (PCR) were amplified. In order to detect different forms of an allele at this locus HaeΙΙΙ restriction enzymes and PCR-RFLP analysis were used. Band patterns clarification was performed using agarose gel electrophoresis. The frequency of genotypes mm, Mm, and MM, were respectively detected, 0, 0.15 and 0.85. The allele frequency for alleles m and M, were respectively, 0.07 and 0.93. The statistical analyses indicated that m allele was significantly associated with body weight. The results of this study suggest that the Myostatin gene possibly is a candidate gene that affects growth traits in Kurdish sheep.

Keywords: GDF8 gene, Kurdi Sheep of Northern Khorasan, polymorphism, weight traits

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Authors: Nabia Siddiqui, Tahira Mohsin Ali, Tanveer Abbas, Abid Hasnain

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The present study proposed the use of different onion peel extracts in a South Asian snacks called ‘sew’. The polyphenols extracted from peels were initially analyzed for their antimicrobial potential and bioactive components following three different extraction systems. A relatively higher level of total phenolic content (TP), total flavonoid (TF) and antioxidant activity was observed for EWE (ethanol and water based) extracts followed by EAAE (ethanol and acetic acid) and WE (water extract) sample. Onion extracts showed ability to inhibit gram-positive as well as gram-negative bacteria. The incorporation of onion peel extracts in sew showed a marked increase in bioactive components. Besides bioactivity, sensory attributes, textural characteristics and storage stability of these snacks containing onion peel extract also significantly improved during the shelf study at ambient temperature for up to two months. Thus, these results justify the utilization of these plant polyphenols in fried snacks.

Keywords: onion peels extract, South Asian snacks, antioxidant capacity, bioactivity

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Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

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In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy C-Means methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc).

Keywords: defuzzification, floating search, fuzzy clustering, Zernike moments

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Authors: Dawood Al Chanti, Alice Caplier

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Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

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Authors: Zyad Elkhadir, Khalid Chougdali, Mohammed Benattou

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Most of the existing intrusion detection systems works on quantitative network traffic data with many irrelevant and redundant features, which makes detection process more time’s consuming and inaccurate. A several feature extraction methods, such as linear discriminant analysis (LDA), have been proposed. However, LDA suffers from the small sample size (SSS) problem which occurs when the number of the training samples is small compared with the samples dimension. Hence, classical LDA cannot be applied directly for high dimensional data such as network traffic data. In this paper, we propose two solutions to solve SSS problem for LDA and apply them to a network IDS. The first method, reduce the original dimension data using principal component analysis (PCA) and then apply LDA. In the second solution, we propose to use the pseudo inverse to avoid singularity of within-class scatter matrix due to SSS problem. After that, the KNN algorithm is used for classification process. We have chosen two known datasets KDDcup99 and NSLKDD for testing the proposed approaches. Results showed that the classification accuracy of (PCA+LDA) method outperforms clearly the pseudo inverse LDA method when we have large training data.

Keywords: LDA, Pseudoinverse, PCA, IDS, NSL-KDD, KDDcup99

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Authors: Toni Maristela C. Estabillo, Michaela V. Matienzo, Mikaela L. Sabangan, Rosette M. Tienzo, Justine L. Bahinting

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This study is about blind watermarking on images with different categories and properties using two algorithms namely, Discrete Wavelet Transform and Patchwork Algorithm. A program is created to perform watermark embedding, extraction and evaluation. The evaluation is based on three watermarking criteria namely: image quality degradation, perceptual transparency and security. Image quality is measured by comparing the original properties with the processed one. Perceptual transparency is measured by a visual inspection on a survey. Security is measured by implementing geometrical and non-geometrical attacks through a pass or fail testing. Values used to measure the following criteria are mostly based on Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The results are based on statistical methods used to interpret and collect data such as averaging, z Test and survey. The study concluded that the combined DWT and Patchwork algorithms were less efficient and less capable of watermarking than DWT algorithm only.

Keywords: blind watermarking, discrete wavelet transform algorithm, patchwork algorithm, digital watermark

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Authors: Sumaira Saleem, Sajjad Hussain, Asma Kashif Shahzad, Hina Shaheen

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This study aims at exploring the relationship between language and ideology and how such relationships are represented in the analysis of spoken texts, following Van Dijk’s Socio Cognitive Model (2002). In this study, it is tried to show that political Talk shows broadcast by Private TV channels are working apparatuses of ideology and store meanings which are not always obvious for readers. This analysis was about the situation created by Arslan Iftkhar, the son of ex-Chief Justice of Pakistan, Iftikhar Muhammad Chaudry and PTI Chief Imran Khan. Arslan Iftikhar submitted an application against Imran Khan that he is not able to become a member of parliament of Pakistan. In the application, he demanded the documents, which are submitted by Imran Khan at the time of Election to the Election Commission of Pakistan. Murad Ali from PTI also submitted an application against PM Nawaz Sharif to the Election Commission of Pakistan for providing the copies. It also suggests that these talk shows mystify the agency of processes by using various strategies. In other words, critical text analyses reveal how these choices enable speakers to manipulate the realizations of agency and power in the representation of action to produce particular meanings which are not always explicit for all readers.

Keywords: ECP, CDA, socio cognitive model, ideology, TV channels, power

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Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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Authors: Jyh-Ping Chen, Yu-Tin Lai

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Wound healing is a complicated process involving overlapping hemostasis, inflammation, proliferation, and maturation phases. Ideal wound dressings can replace native skin functions in full thickness skin wounds through faster healing rate and also by reducing scar formation. Poly(lactic-co-glycolic acid) (PLGA) is an U.S. FDA approved biodegradable polymer to be used as ideal wound dressing material. Several in vitro and in vivo studies have demonstrated the effectiveness of curcumin in decreasing the release of inflammatory cytokines, inhibiting enzymes associated with inflammations, and scavenging free radicals that are the major cause of inflammation during wound healing. Heparin has binding affinities to various growth factors. With the unique and beneficial features offered by those molecules toward the complex process of wound healing, we postulate a composite wound dressing constructed from PLGA, curcumin and heparin would be a good candidate to accelerate scarless wound healing. In this work, we use electrospinning to prepare curcumin-loaded aligned PLGA nanofibrous membranes (PC NFMs). PC NFMs were further subject to oxygen plasma modification and surfaced-grafted with heparin through carbodiimide-mediated covalent bond formation to prepare curcumin-loaded PLGA-g-heparin (PCH) NFMs. The nanofibrous membranes could act as three-dimensional scaffolds to attract fibroblast migration, reduce inflammation, and increase wound-healing related growth factors concentrations at wound sites. From scanning electron microscopy analysis, the nanofibers in each NFM are with diameters ranging from 456 to 479 nm and with alignment angles within  0.5°. The NFMs show high tensile strength and good water absorptivity and provide suitable pore size for nutrients/wastes transport. Exposure of human dermal fibroblasts to the extraction medium of PC or PCH NFM showed significant protective effects against hydrogen peroxide than PLGA NFM. In vitro wound healing assays also showed that the extraction medium of PCH NFM showed significantly better migration ability toward fibroblasts than PC NFM, which is further better than PLGA NFM. The in vivo healing efficiency of the NFMs was further evaluated by a full thickness excisional wound healing diabetic rat model. After 14 days, PCH NFMs exhibits 86% wound closure rate, which is significantly different from other groups (79% for PC and 73% for PLGA NFM). Real-time PCR analysis indicated PC and PCH NFMs down regulated anti-oxidative enzymes like glutathione peroxidase (GPx) and superoxide dismutase (SOD), which are well-known transcription factors involved in cellular inflammatory responses to stimuli. From histology, the wound area treated with PCH NFMs showed more vascular lumen formation from immunohistochemistry of α-smooth muscle actin. The wound site also had more collagen type III (65.8%) expression and less collagen type I (3.5%) expression, indicating scar-less wound healing. From Western blot analysis, the PCH NFM showed good affinity toward growth factors from increased concentration of transforming growth factor-β (TGF-β) and fibroblast growth factor-2 (FGF-2) at the wound site to accelerate wound healing. From the results, we suggest PCH NFM as a promising candidate for wound dressing applications.

Keywords: Curcumin, heparin, nanofibrous membrane, poly(lactic-co-glycolic acid) (PLGA), wound dressing

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Authors: Sh. Najari Moghadam, M. Qomi, F. Raofie, J. Khadiv

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In this study, a liquid phase microextraction by hollow fiber (HF-LPME) combined with high performance liquid chromatography-UV detector was applied to preconcentrate and determine trace levels of Cyproheptadine in human urine and plasma samples. Cyproheptadine was extracted from 10 mL alkaline aqueous solution (pH: 9.81) into an organic solvent (n-octnol) which was immobilized in the wall pores of a hollow fiber. Then, it was back-extracted into an acidified aqueous solution (pH: 2.59) located inside the lumen of the hollow fiber. This method is simple, efficient and cost-effective. It is based on pH gradient and differences between two aqueous phases. In order to optimize the HF-LPME, some affecting parameters including the pH of donor and acceptor phases, the type of organic solvent, ionic strength, stirring rate, extraction time and temperature were studied and optimized. Under optimal conditions enrichment factor, limit of detection (LOD) and relative standard deviation (RSD(%), n=3) were up to 112, 15 μg.L−1 and 2.7, respectively.

Keywords: biological samples, cyproheptadine, hollow fiber, liquid phase microextraction

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Authors: Haitham Qaralleh, Syed Z. Idid, Shahbudin Saad, Deny Susanti, Osama Althunibat

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This study was carried out to isolate the active antimicrobial compounds from Neopetrosia exigua using bio-guided assay isolation against Staphylococcus aureus. N. exigua was extracted using methanol and subjected to liquid-liquid extraction using solvents with different polarity (n-hexane, carbon tetrachloride, dichloromethane, n-butanol and water). Purification of the active components of n-butanol and dichloromethane fractions was done using Sephadex LH-20 and reverse phase chromatography. Based on the biological guided fractionation results, dichloromethane and n-butanol fractions showed the highest antimicrobial activity. Purification of the active components of n-butanol and dichloromethane fractions yielded three compounds. The structure of the isolated compounds were elucidated and found to be 5-hydroxy-1H-indole-3-carboxylic acid methyl ester, cyclo-1`-demethylcystalgerone and avarol derivative. Avarol was showed potent bactericidal effect against S. aureus. N. exigua appears to be rich source of natural antimicrobial agents. Further studies are needed to investigate the mode of action of these compounds.

Keywords: antimicrobial, avarol, Neopetrosia exigua, Staphylococcus aureus

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Authors: Newton Rathnasiri Ranaweera Kalu Arachchige

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Academics argue that Greek myths and legends have had an influence on Buddhist stories: Jataka tales, Theri Gata (Psalms of older Buddhist nuns), and even Mahavansa (a Sri Lankan historical chronicle). However, this article asserts that there is evidence in Sophocles King Oedipus to argue that the Buddha’s life story and key Buddhist concepts have influenced pre-Christian Greek philosophy and literature, especially Sophocles’ King Oedipus. When reading the text with the notion that there could be intertextual relationships or new texts are built on the existing texts and discourses, the reader may see that Sophocles’ play contains incidents that remind them of the special occasions of the Buddha’s life, his utterances and the key Buddhist concepts such as the truth of suffering, cessation of suffering, the three poisons (greed, hatred, and delusion), and finding the truth within one’s own self. The present intertextual study explored only the special occasions of the Buddha’s life to make it more focused and found that Sophocles alludes to the Buddha’s life story in his attempt to raise a moral culprit to a moral hero with higher moral values. This article, however, acknowledges that one needs to cross-check the other historical and philosophical references when claiming that Sophocles has had influence from the Buddha’s life story in King Oedipus.

Keywords: Buddhism, the Buddha’s life story, King Oedipus, Greece, tragedy, Sri Lanka

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Authors: Austin Belfiori, Kevin Rinek, Zach Barcroft, Jennifer Berglind

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Diet influences the composition of the gut microbiota and host's health. Disruption of the balance among the microbiota, epithelial cells, and resident immune cells in the intestine is involved in the pathogenesis of inflammatory bowel disease (IBD). To study the role of gut microbiota in intestinal inflammation, the microbiome of control mice (C57BL6) given a gluten-containing standard diet versus C57BL6 mice given the gluten-free (GF) feed (n=10 in each group) was examined. All mice received the 3% DSS for 5 days. Throughout the study, feces were collected and processed for DNA extraction and MiSeq Illumina sequencing of V4 region of bacterial 16S rRNA gene. Alpha and beta diversities and compositional differences at phylum and genus levels were determined in intestinal microbiota. The mice receiving the GF diet showed a significantly increased abundance of Firmicutes and a decrease of Bacteroides and Lactobacillus at phylum level. Therefore, the gluten free diet led to reductions in beneficial gut bacteria populations. These findings indicate a role of wheat gluten in dysbiosis of the intestinal microbiota.

Keywords: gluten, colitis, microbiota, DSS, dextran sulphate sodium

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Authors: Mohammed Hakim Jafferali, Balaje Vijayaraghavan, Ricardo A. Figueroa, Ellinor Crafoord, Veronica J. Larsson, Einar Hallberg, Santhosh Gudise

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The nuclear envelope which surrounds the chromatin of eukaryotic cells contains more than a hundred transmembrane proteins. Mutations in some genes encoding nuclear envelope proteins give rise to human diseases including neurological disorders. The function of many nuclear envelope proteins is not well established. This is partly because nuclear envelope proteins and their interactions are difficult to study due to the inherent resistance to extraction of nuclear envelope proteins. We have developed a novel method called MCLIP, to identify interacting partners of nuclear envelope proteins in live cells. Using MCLIP, we found three new binding partners of the inner nuclear membrane protein Samp1: the intermediate filament protein Lamin B1, the LINC complex protein Sun1 and the G-protein Ran. Furthermore, using in vitro studies, we show that Samp1 binds both Emerin and Ran directly. We have also studied the interaction between Samp1 and Ran in detail. The results show that the Samp1 binds stronger to RanGTP than RanGDP. Samp1 is the first transmembrane protein known to bind Ran and it is tempting to speculate that Samp1 may provide local binding sites for RanGTP at membranes.

Keywords: MCLIP, nuclear envelope, ran, Samp1

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Authors: Krishnanunni S.

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The COVID-19 Pandemic has had an impact on every part of our lives, and the film industry is no exception. The restrictions the pandemic has brought made filmmakers confine their films to limited spaces. In India, Malayalam cinema was the first to incorporate the pandemic into its stories and started producing films within existing constraints. The purpose of this study was to study how the limited location storytelling concept influenced Malayalam independent and lockdown films. To answer this question, the three of the most popular films that we shot during the pandemic: The Great Indian Kitchen, Joji and Joyful Mystery, were dissected through text analysis and in-depth interviews were conducted with the makers of The Great Indian Kitchen and Joyful Mystery. The study revealed that the pandemic had had an influence on the way filmmakers visualize their stories and shoot them, especially while working within the restrictions of the pandemic. It was also observed that working with limited locations was the only way for filmmakers to make films during the times of pandemic. But rather than a hindrance to their work, filmmakers saw it as a new possibility to create in times of confinement. The findings of this study expanded the work of previous researchers about films shot in limited locations and the significant changes the pandemic has brought to the film industry.

Keywords: limited location storytelling, pandemic, pandemic restrictions, lockdown cinema, pandemic films, Malayalam cinema, OTT revolution, cinema, films

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Authors: Javed Khan, Aamir Saeed Malik, Nidal Kamel, Sarat Chandra Dass, Azura Mohd Affandi

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Low contrast images can result from the wrong setting of image acquisition or poor illumination conditions. Such images may not be visually appealing and can be difficult for feature extraction. Contrast enhancement of color images can be useful in medical area for visual inspection. In this paper, a new technique is proposed to improve the contrast of color images. The RGB (red, green, blue) color image is transformed into normalized RGB color space. Adaptive histogram equalization technique is applied to each of the three channels of normalized RGB color space. The corresponding channels in the original image (low contrast) and that of contrast enhanced image with adaptive histogram equalization (AHE) are morphed together in proper proportions. The proposed technique is tested on seventy color images of acne patients. The results of the proposed technique are analyzed using cumulative variance and contrast improvement factor measures. The results are also compared with decorrelation stretch. Both subjective and quantitative analysis demonstrates that the proposed techniques outperform the other techniques.

Keywords: contrast enhacement, normalized RGB, adaptive histogram equalization, cumulative variance.

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Authors: N. Mezıou-Cheboutı, A. Merabet, N. Behidj, F. Z. Bissaad

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The Algeria by its location, offers a rich and diverse vegetation. A large number of aromatic and medicinal plants grow spontaneously. The interest in these plants has continued to grow in recent years. Their particular properties due to the essential oil fraction can be utilized to treat microbial infections. To this end, and in the context of the valuation of the Algerian flora, we became interested in the species of the family Lamiaceae which is one of the most used as a global source of spices and extracts strong families antimicrobial potency. The plant on which we have based our choice is a species of sage "Salvia officinalis" from the Isser localized region within the province of Boumerdes. This work focuses on the study of the antimicrobial activity of essential oil extracted from the leaves of salvia officinalis. The extraction is carried out by HE hydrodistillation and reveals a yield of 1.06℅. The study of the antimicrobial activity of the essential oil by the method of at aromatogramme shown that Gram positive bacteria are most susceptible (Staphylococcus aureus and Bacillus subtilis) with a strong inhibition of growth. The yeast Candida albicans fungus Aspergillus niger and have shown moderately sensitive.

Keywords: Salvia officinalis, steam distillation, essential oil, aromatogram, anti-microbial activity

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Authors: David Tresner-Kirsch

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Reconciling patient medication lists from multiple sources is a critical task supporting the safe delivery of patient care. Manual reconciliation is a time-consuming and error-prone process, and recently attempts have been made to develop efficiency- and safety-oriented automated support for professionals performing the task. An important capability of any such support system is automated alignment – finding which medications from a list correspond to which medications from a different source, regardless of misspellings, naming differences (e.g. brand name vs. generic), or changes in treatment (e.g. switching a patient from one antidepressant class to another). This work describes a new algorithmic solution to this alignment task, using a greedy matching approach based on string similarity, edit distances, concept extraction and normalization, and synonym search derived from the RxNorm nomenclature. The accuracy of this algorithm was evaluated against a gold-standard corpus of 681 medication records; this evaluation found that the algorithm predicted alignments with 99% precision and 91% recall. This performance is sufficient to support decision support applications for medication reconciliation.

Keywords: clinical decision support, medication reconciliation, natural language processing, RxNorm

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Authors: Vahid Bayrami Rad

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In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

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Authors: Ven Pothupitiye Thilakasiri

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The Ādittapariyāya Sutta, also known as the Fire Sermon is an important Buddhist text that addresses the nature of sensual pleasures and attachment through the metaphor of fire. Eliot makes use of this in his epic poem The Waste Land. Though scholars have studied Eliot‘s long poem for traces of eastern philosophy, no scholars have touched upon the idea of how the Adittapariyaya Sutta has enabled the meaning making endeavor of the poem. The present study attempts to address this research gap by undertaking a critical analysis of the Fire Sermon of The Waste Land by undertaking an interdisciplinary study of the poem using two methods—a literary and Buddhist reading methods, namely objective corelative and the three-pillared Buddhist ideas of Anicca (impermanence), Dukkha (suffering) and Anatha (No-self). Thus, the study explores the Ādittapariyāya Sutta’s thematic concerns of impermanence, suffering and no-self within the context of The Waste Land. The setting of the poem symbolizes spiritual desolation and existential crisis. By comparing Sutta‘s teachings with modern existential concerns, which is depicted in T.S. Eliot‘s The Waste Land, the analysis emphasizes the relevance of Buddhist insights to contemporary issues of meaning and disillusio

Keywords: Adittapariyaya Sutta, Objective correlative, Eastern Philosophy, Sensual pleasures

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Authors: Yung-Chen Hsu, Juan Hernandez, W. T. Evert Ting, Dawit Gizachew

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Mycotoxin contamination of foods and feeds poses a high risk for human and animal health. Ochratoxin A (OTA) is a ubiquitous mycotoxin produced by Aspergillus and Penicillium fungi. It exhibits nephrotoxicity, teratogenicity, mutagenicity, and immunotoxicity in both humans and animals. OTA has been detected in foods such as cereals, coffee, grapes, cocoa, wine, and spices. Consumption of food contaminated with OTA has been linked to kidney and liver diseases. Niger (Guizotia abyssinica) is an oil seed that is used for extracting cooking oil in countries like Ethiopia and India. The seed cake (a byproduct from oil extraction) is also used as dairy cattle feed in Ethiopia. It is also exported to North America and Europe to be used mainly as bird feed. To our knowledge, there have been no studies on the growth and production of OTA on niger seeds. In this study, the environment conditions that support OTA production including effects of water activity, temperature, and incubation time on growth and OTA production by A. fresenii and A. sulphureus were investigated.

Keywords: mycotoxin, ochratoxin A, aspergillus, niger seed

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Authors: Allmin Susaiyah, Aki Härmä, Milan Petković

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Automatic generation of insights from data using insight mining systems (IMS) is useful in many applications, such as personal health tracking, patient monitoring, and business process management. Existing IMS face challenges in controlling insight extraction, scaling to large databases, and generalising to unseen domains. In this work, we propose a hybrid approach consisting of rule-based and neural components for generating insights from data while overcoming the aforementioned challenges. Firstly, a rule-based data 2CNL component is used to extract statistically significant insights from data and represent them in a controlled natural language (CNL). Secondly, a BERTSum-based CNL2NL component is used to convert these CNLs into natural language texts. We improve the model using task-specific and domain-specific fine-tuning. Our approach has been evaluated using statistical techniques and standard evaluation metrics. We overcame the aforementioned challenges and observed significant improvement with domain-specific fine-tuning.

Keywords: data mining, insight mining, natural language generation, pre-trained language models

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Authors: Fernanda Conforto de Oliveira

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The International Monetary Fund (IMF) has a central role in global financial governance as the world’s leading crisis lender. Its practice of conditional lending – conditioning loans on the implementation of economic policy adjustments – is the primary lever by which the institution interacts with and influences the policy choices of member countries and has been a key topic of interest to scholars and public opinion. However, empirical evidence about the economic and (geo)political determinants of IMF lending behavior remains inconclusive, and no model that explains IMF policies has been identified. This research moves beyond panel analysis to focus on financial negotiations for the first IMF programs in Argentina and Brazil in the early post-war period. It seeks to understand why negotiations achieved distinct objectives: Argentinean officials cooperated and complied with IMF policies, whereas their Brazilian counterparts hesitated. Using qualitative and automated text analysis, this paper analyses the hypothesis about whether a differential IMF treatment could help to explain these distinct outcomes. This paper contributes to historical studies on IMF-Latin America relations and the broader literature in international policy economy about IMF policies.

Keywords: international monetary fund, international history, financial history, Latin American economic history, natural language processing, sentiment analysis

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Authors: Yanmeng Liu

Abstract:

This article analyzes and compares the linguistic differences between machine translation and manual translation, through a case study of the book Gone with the Wind. As an important carrier of human feeling and thinking, the literature translation poses a huge difficulty for machine translation, and it is supposed to expose distinct translation features apart from manual translation. In order to display linguistic features objectively, tentative uses of computerized and statistical evidence to the systematic investigation of large scale translation corpora by using quantitative methods have been deployed. This study compiles bilingual corpus with four versions of Chinese translations of the book Gone with the Wind, namely, Piao by Chunhai Fan, Piao by Huairen Huang, translations by Google Translation and Baidu Translation. After processing the corpus with the software of Stanford Segmenter, Stanford Postagger, and AntConc, etc., the study analyzes linguistic data and answers the following questions: 1. How does the machine translation differ from manual translation linguistically? 2. Why do these deviances happen? This paper combines translation study with the knowledge of corpus linguistics, and concretes divergent linguistic dimensions in translated text analysis, in order to present linguistic deviances in manual and machine translation. Consequently, this study provides a more accurate and more fine-grained understanding of machine translation products, and it also proposes several suggestions for machine translation development in the future.

Keywords: corpus-based analysis, linguistic deviances, machine translation, statistical evidence

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Authors: R. Bouhennache, T. Bouden, A. A. Taleb, A. Chaddad

Abstract:

In this paper we propose a method to map the urban areas. The method uses an arithmetic calculation processed from the land features indexes and Tasseled cap transformation TC of multi spectral Thematic Mapper Landsat TM image. For this purpose the derived indexes image from the original image such SAVI the soil adjusted vegetation index, UI the urban Index, and EBBI the enhanced built up and bareness index were staked to form a new image and the bands were uncorrelated, also the Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) supervised classification approaches were first applied on the new image TM data using the reference spectra of the spectral library and subsequently the four urban, vegetation, water and soil land cover categories were extracted with their accuracy assessment.The urban features were represented using a logic calculation applied to the brightness, UI-SAVI, NDBI-greenness and EBBI- brightness data sets. The study applied to Blida and mentioned that the urban features can be mapped with an accuracy ranging from 92 % to 95%.

Keywords: EBBI, SAVI, Tasseled Cap Transformation, UI

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Authors: Fani Sakellariadou, Danae Antivachis

Abstract:

Purpose of this paper is to evaluate the environmental status of a coastal Mediterranean lake, named Koumoundourou, located in the northeastern coast of Elefsis Bay, in the western region of Attiki in Greece, 15 km far from Athens. It is preserved from ancient times having an important archaeological interest. Koumoundourou lake is also considered as a valuable wetland accommodating an abundant flora and fauna, with a variety of bird species including a few world’s threatened ones. Furthermore, it is a heavily modified lake, affected by various anthropogenic pollutant sources which provide industrial, urban and agricultural contaminants. The adjacent oil refineries and the military depot are the major pollution providers furnishing with crude oil spills and leaks. Moreover, the lake accepts a quantity of groundwater leachates from the major landfill of Athens. The environmental status of the lake results from the intensive land uses combined with the permeable lithology of the surrounding area and the existence of karstic springs which discharge calcareous mountains. Sediment samples were collected along the shoreline of the lake using a Van Veen grab stainless steel sampler. They were studied for the determination of the total metal content and the metal fractionation in geochemical phases as well as the characterization of the dissolved organic matter (DOM). These constituents have a significant role in the ecological consideration of the lake. Metals may be responsible for harmful environmental impacts. The metal partitioning offers comprehensive information for the origin, mode of occurrence, biological and physicochemical availability, mobilization and transport of metals. Moreover, DOM has a multifunctional importance interacting with inorganic and organic contaminants leading to biogeochemical and ecological effects. The samples were digested using microwave heating with a suitable laboratory microwave unit. For the total metal content, the samples were treated with a mixture of strong acids. Then, a sequential extraction procedure was applied for the removal of exchangeable, carbonate hosted, reducible, organic/sulphides and residual fractions. Metal content was determined by an ICP-MS (Perkin Elmer, ICP MASS Spectrophotometer NexION 350D). Furthermore, the DOM was removed via a gentle extraction procedure and then it was characterized by fluorescence spectroscopy using a Perkin-Elmer LS 55 luminescence spectrophotometer equipped with the WinLab 4.00.02 software for data processing (Agilent, Cary Eclipse Fluorescence). Mono dimensional emission, excitation, synchronous-scan excitation and total luminescence spectra were recorded for the classification of chromophoric units present in the aqueous extracts. Total metal concentrations were determined and compared with those of the Elefsis gulf sediments. Element partitioning showed the anthropogenic sources and the contaminant bioavailability. All fluorescence spectra, as well as humification indices, were evaluated in detail to find out the nature and origin of DOM. All the results were compared and interpreted to evaluate the environmental quality of Koumoundourou lake and the need for environmental management and protection.

Keywords: anthropogenic contaminant, dissolved organic matter, lake, metal, pollution

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