Search results for: extraction wound

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: 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: 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: Darshana Rathod, Kirtikumar Rathod, Kamlesh Kumari, Abhilasha Motghare

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Background and Aims: Hypospadias is one of the common congenital anomalies in males. Various modalities are used for pain management, including caudal, penile, pudendal, ring blocks, and systemic analgesics. There has yet to be a consensus regarding the most effective and safe analgesic method for controlling pain in these children. We planned this study to determine our institute's pain management practices for hypospadias surgeries. Material and Methods: This retrospective cohort study reviewed 150 children with hypospadias undergoing surgery from January 2020 to December 2023. Data regarding the mode of pain management, postoperative opioid requirement, PACU discharge, and complications was collected from the records. Results: For postoperative pain, 33 (22%) children received caudal block, 60 (40%) penile block, and 57 (38%) were managed by intravenous analgesics. A significant difference was found in the three groups, with the IV analgesic group requiring significantly higher opioid boluses in PACU [43 (75.4%) required two boluses (p < 0.05)]. The difference in PACU discharge time among the three groups was statistically significant (p< 0.05), with IV analgesics groups having the highest (55 mins [47, 60]), the Caudal group at 35mins (30, 40), and the dorsal penile block group at 35mins (25, 40). There was no significant difference in complications like edema, meatal stenosis, urethra-cutaneous fistula, or wound dehiscence among all three groups. Conclusion: Intravenous analgesics and regional blocks like caudal and penile blocks are the common pain management modalities in our institute. The regional blocks are effective in managing pain in the postoperative period and are not significantly associated with complications.

Keywords: caudal block, hypospadias, pain management, penile block

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Authors: Enjie Xu, Zhen Huang, Kunpeng Zhu, Jianping Hu, Xiaolong Ma, Yongjie Wang, Jiazhuang Zhu, Chunlin Zhang

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Abstract: Hypoxia and dedifferentiation of osteosarcoma (OS) cells leads to poor prognosis. We plan to identify the role of hypoxia on dedifferentiation and the associated signaling pathways. We performed a sphere formation assay and determined spheroid cells as dedifferentiated cells by detecting stem cell-like markers. RNAi assay was used to explore the expression relationship between hypoxia inducible factor 1 subunit alpha (HIF1A) and platelet derived growth factor receptor beta (PDGFRB). We obtained PDGFRB knockdown and overexpression cells through lentiviral infection experiments and the effects of PDGFRB on cytoskeleton rearrangement and cell adhesion were explored by immunocytochemistry. Wound-healing experiments, transwell assays, and animal trials were employed to investigate the effect of PDGFRB on OS metastasis. Dedifferentiated OS cells were found to exhibit high expression of HIF1A and PDGFRB, and HIF1A promoted the expression of PDGFRB, subsequently activated ras homolog family member A (RhoA), and increased the phosphorylation of myosin light chain (MLC). PDGFRB also enhanced the phosphorylation of focal adhesion kinase (FAK). The OS cell morphology and vinculin distribution were altered by PDGFRB. PDGFRB also promoted cell dedifferentiation and had a significant impact on the metastasis of OS cells both in vitro and in vivo. Our results demonstrated that HIF1A up-regulated PDGFRB under hypoxic conditions, and PDGFRB regulated the actin cytoskeleton by activating RhoA and subsequently phosphorylating MLC, thereby promoting OS dedifferentiation and pulmonary metastasis.

Keywords: osteosarcoma, dedifferentiation, metastasis, cytoskeleton rearrangement, PDGFRB, hypoxia

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Authors: G. Wojcik, J. Gindlhuber, A. Syarif, K. Hoetzenecker, P. Bohm, P. Vesely, V. Biasin, G. Kwapiszewska

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Pulmonary fibrosis is a rare disease where uncontrolled wound healing processes damage the lung structure. Intensive changes within the extracellular matrix (ECM) and its interaction with fibroblasts have a major role in pulmonary fibrosis development. Among others, collagen is one of the main components of the ECM, and it is important for lung structure. In IPF, constant production of collagen by fibroblast, through TGFβ1-SMAD2/3 pathways, leads to an uncontrolled deposition of matrix and hence lung remodeling. Abnormal changes in lipid production, alterations in fatty acids (FAs) metabolism, enhanced oxidative stress, and lipid peroxidation in fibrotic lung and fibrotic fibroblasts have been reported; however, the interplay between the collagen and lipids is not yet established. One of the FAs influx regulators is Angiopoietin-like 4 (ANGPTL4), which inhibits lipoprotein lipase work, decreasing the availability of FAs. We hypothesized that altered lipid composition or availability could have the capability to influence the phenotype of different fibroblast populations in the lung and hence influence lung fibrosis. To prove our hypothesis, we aim to investigate lipids and their influence on human, animal, and in vitro levels. In the bleomycin model, treatment with the well-known metabolic drugs Rosiglitazone or Metformin significantly lower collagen production. Similar results were noticed in ANGPTL4 KO animals, where the KO of ANGPTL4 leads to an increase of FAs availability and lower collagen deposition after the bleomycin challenge. Currently, we study the treatment of different FAs on human lung para fibroblasts (hPF) isolated from donors. To understand the lipid composition, we are collecting human lung tissue from donors and pulmonary fibrosis patients for Liquid chromatography-mass spectrometry. In conclusion, our results suggest the lipid influence on collagen deposition during lung fibrosis, but further research needs to be conducted to understand the matter of this relationship.

Keywords: collagen, fibroblasts, lipidomics, lung, pulmonary fibrosis

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Authors: S. Vasailor, C. Rattanakawin

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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: 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

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Authors: Younmin Shin, Jin Kyu Kim, Mirim Jin, Jeong June Choi

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Demilitarized Zone (DMZ) is a peace region located between South and North Korea border to avoid accidental armed conflict. Because human accessing to the area was forced to be prohibited for more than 60 years, DMZ is one of the cleanest land keeping wild lives as nature itself in South Korea. In this study, we evaluated the biological efficacies of plants (SS, PC, and AR) inhabiting in DMZ for the development of functional cosmetics. First, we tested the cytotoxicity of plant extracts in keratinocyte and melanocyte, which are the major cell components of skin. By 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay with the cell lines, we determined the safety concentrations of the extracts for the efficacy tests. Next, we assessed the anti-wrinkle cosmetic function of SS by demonstrating that SS treatment decreased the expression of Matrix metalloproteinase-1 (MMP-1) in UV-irradiated keratinocytes via real-time PCR. The suppressive effect of SS was greatly potentiated by combination with other DMZ-inhabiting plants, PC and AR. The expression of tyrosinase, which is one the main enzyme that producing melanin in melanocyte, was also down-regulated by the DMZ-inhabiting SS extract. Wound healing activity was also investigated by in vitro test with HaCat cell line, a human fibroblast cell line. All the natural materials extracted form DMZ habiting plants accelerated the recovery of the cells. These results suggested that DMZ is a treasure island of functional plants and DMZ-inhabiting natural products are warranted to develop functional cosmetic materials. This study was carried out with the support of R&D Program for Forest Science Technology (Project No. 2017027A00-1819-BA01) provided by Korea Forest Service (Korea Forestry Promotion Institute).

Keywords: anti-wrinkle, Demilitarized Zone, functional cosmetics, whitening

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Authors: F. Fernandes, C. Poleto

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This paper aims at assessing the concentrations of heavy metals and the isotopic composition of lead ²¹⁰Pb in different fractions of sediment produced in the watershed that makes up the Mãe d'água dam and thus characterizing the distribution of metals along the sedimentary column and inferencing in the urbanization of the same process. Sample collection was carried out in June 2014; eight sediment cores were sampled in the lake of the dam. For extraction of the sediments core, a core sampler “Piston Core” was used. The trace metal concentrations were determined by conventional atomic absorption spectrophotometric methods. The samples were subjected to radiochemical analysis of ²¹⁰Po. ²¹⁰Pb activity was obtained by measuring ²¹⁰Po activity. The chronology was calculated using the constant rate of supply (CRS). ²¹⁰Pb is used to estimate the sedimentation rate.

Keywords: ²¹⁰Pb dating method, heavy metal, lakes urban, pollution history

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Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

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China launched satellite GF-2 in 2014. This study deals with comparing nearest neighbor object-based classification and neural network classification methods for classification of the fused GF-2 image. Firstly, rectification of GF-2 image was performed. Secondly, a comparison between nearest neighbor object-based classification and neural network classification for classification of fused GF-2 was performed. Thirdly, the overall accuracy of classification and kappa index were calculated. Results indicate that nearest neighbor object-based classification is better than neural network classification for urban mapping.

Keywords: GF-2 images, feature extraction-rectification, nearest neighbour object based classification, segmentation algorithms, neural network classification, multilayer perceptron

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Authors: Zineb Nougrara

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In this paper, we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We, therefore, have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.

Keywords: satellite image, road network, nodes, image analysis and processing

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Authors: Devinder Kaur Sugga, Ekamdeep Kaur, Jaspreet Kaur, C. Rajesh, Preeti Rajesh, Harsimran Kaur

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Withanolides are steroidal lactones and are highly oxygenated phytoconstituents that can be developed as potential anti-carcinogenic agents. The two main withanolides, namely Withaferin A and Withanolides D, have been extensively studied for their pharmacological activities. Both these withanolides are present in the Withania somnifera (WS) leaves belonging to the family Solanaceae, also known as “Indian ginseng .”In this study effects of WS leaf extract on the MCF7 breast cancer cell line were investigated by performing a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay to evaluate the cytotoxic effects and in vitro wound-healing assay to study the effect on cancer cell migration. Our data suggest WS extracts have cytotoxic effects and are effective anti-migrating agents and thus can be a source of potential candidates for the development of potential agents against metastasis. Thus, it can be a source of potential candidates for the development of potential agents against metastasis. Insight into these results, the in-silico approach to identify the possible protein targets interacting with withanolides was taken. Protein kinase C alpha (PKCα) was among the selected 5 top-ranked target proteins identified by the Swiss Target Prediction tool. PKCα is known to promote the growth and invasion of cancer cells and is being evaluated as a prognostic biomarker and therapeutic target in clinically aggressive tumors. Molecular docking of Withaferin A and Withanolides D was performed using AutoDock Vina. Both the bioactive compounds interacted with PKCα. The targets predicted using this approach will serve as leads for the possible therapeutic potential of withanolides, the bioactive ingredients of WS extracts, as anti-cancer drugs.

Keywords: withania somnifera, withaferin A, withanolides D, PKCα

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Authors: M. A. Ben Messaoud, A. Bouzid, N. Ellouze

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Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The multi-scale product is based on making the product of the speech wavelet transform coefficients at three successive dyadic scales. We have evaluated our method on the Keele database. Experimental results show the effectiveness of our method presenting a good performance. It shows that the two simple features can find word boundaries, and extracted the segments of the clean speech.

Keywords: multiscale product, spectral centroid, speech segmentation, zero crossings rate

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Authors: Mustapha Mahmoud, Fouzia Toumi Benali, Mohamed Benyahia, Sofiane Bouazza

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This work focuses on the influences of biological and chemical parameters on the phenolic compounds such as flavonoids and tannins in different medicinal plants in western Algeria (Papaver rhoeas, Daphnegnidium, Lavandula multifida, Lavandula dentata, Lavandula stoicha, ...). Thus we look the difference between species of the same genus, difference between the different organs of the same species, the influence of environment all temperature influences, time, percentage of solvent on the extraction. Quantification of the phenolic compounds was performed by spectrophotometric method then treated with statistics tools such as variance analysis, multivariant analyzes, response surface methodology). The results show that the polyphenols are influenced by the parameters mentioned.

Keywords: polyphenols, influences, medicinal plants, west Algeria

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Authors: Hilary Rutto

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The investigation was aimed at determining the extent at which the zinc will be extracted from secondary sources generated from galvanising process using dilute sulphuric acid under controlled laboratory conditions of temperature, solid-liquid ratio, and agitation rate. The leaching experiment was conducted for a period of 2 hours and to total zinc extracted calculated in relation to the amount of zinc dissolved at a unit time in comparison to the initial zinc content of the zinc ash. Sulphuric acid was found to be an effective leaching agent with an overall extraction of 91.1% when concentration is at 2M, and solid/liquid ratio kept at 1g/200mL leaching solution and temperature set at 65ᵒC while slurry agitation is at 450rpm. The leaching mechanism of zinc ash with sulphuric acid was conformed well to the shrinking core model.

Keywords: leaching, kinetics, shrinking core model, zinc slag

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Authors: Lamidi Lawal Aduozava

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Masquerade tradition is an indigenous culture of the Anetuno an extraction of the Ebira referred to as Ebira chao. This paper seeks to make aesthetic analysis of the masquerades in terms of their costumes and socio-cultural significance. To this end, the study examined and documented the functions and roles of Anipo and Idowo masquerades in terms of therapeutic, economic, prophetic and divination, entertainment, and funeral functions to the owner community(Eziobe group of families) in Igarra, Edo State of Nigeria, West Africa. For the purpose of data collection, focus group discussion, participatory, visual and observatory methods of data collection were used. All the data collected were aesthetically, descriptively and historically analyzed.

Keywords: Aesthetics, , Costume, , Masquerades, , Significance.

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Authors: Maria Reichenber Arcilla

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Objective: To determine the risk factors for maternal and neonatal complications associated with operative vaginal deliveries. Methods: A retrospective chart review of 435 patients who underwent operative vaginal deliveries was done. Patient profiles – age, parity, AOG, duration of labor – and outcomes – birthweight, maternal and neonatal complications - were tabulated and multivariable analysis and logistic regression were performed using SPSS® Statistics Base. Results and Conclusion: There was no significant difference in the incidence of maternal and neonatal complications between those that underwent vacuum and forceps extraction. Among the variables analysed, parity and duration of labor reached statistical significance. The odds of maternal complications were 3 times higher among nulliparous patients. Neonatal complications were seen in those whose labor lasted more than 9 hours.

Keywords: operative vaginal deliveries, maternal, neonatal, morbidity

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Authors: A. A Warra, S. Fatima

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The experimental investigation revealed that the hexane extract of onion seed oil has acid value, iodine value, peroxide value, saponification value, relative density and refractive index of 0.03±0.01 mgKOH/g, 129.80±0.21 gI2/100g, 3.00± 0.00 meq H2O2 203.00±0.71 mgKOH/g, 0.82±0.01and 1.44±0.00 respectively. The percentage yield was 50.28±0.01%. The colour of the oil was light green. We restricted our GC-MS spectra interpretation to compounds identification, particularly fatty acids and they are identified as palmitic acid, linolelaidic acid, oleic acid, stearic acid, behenic acid, linolenic acid and eicosatetraenoic acid. The pH , foam ability (cm³), total fatty matter, total alkali and percentage chloride of the onion oil soap were 11.03± 0.02, 75.13±0.15 (cm³), 36.66 ± 0.02 %, 0.92 ± 0.02% and 0.53 ± 0.15 % respectively. The texture was soft and the colour was lighter green. The results indicated that the hexane extract of the onion seed oil has potential for cosmetic industries.

Keywords: onion seeds, soxhlet extraction, physicochemical, GC-MS, cold saponification

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Authors: Ashok K. Gupta

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Over the past few decades, since the bio-engineering revolution, autologous cell therapy (ACT) has become a rapidly evolving field. Currently, this form of therapy has broad applications in modern medicine and plastic surgery, ranging from the treatment/improvement of wound healing to life-saving operations. A study was conducted on 50 patients having to disfigure, and deform post burn scars and was treated by injection of extracted, refined adipose tissue grafts with their unique stem cell properties. To compare the outcome, a control of 20 such patients was treated with conventional skin or soft-tissue flaps or skin grafting, and a control of 10 was treated with more advanced microsurgical techniques such as Pre-fabricated flaps/pre laminated flaps / free flaps. Assessment of fat volume and survival post- follow up period was done by radiological aid, using MRI and clinically (Survival of the autograft and objective parameters for scar elasticity were evaluated skin elasticity parameters 3 to 9 months postoperatively). Recently, an enzyme that is involved in collagen crosslinking in fibrotic tissue, lysyl hydroxylase (LH2), was identified. This enzyme is normally active in bone and cartilage but hardly in the skin. It has been found that this enzyme is highly expressed in scar tissue and subcutaneous fat; this is in contrast to the dermis, where the enzyme is hardly expressed. Adipose tissue-derived stem cell injections are an effective method in the treatment of various extensive post-burn scar deformities that makes it possible to re-create the lost sub-dermal tissue for improvement in the function of involved joint movements.

Keywords: adipose tissue-derived stem cell injections, treatment of various extensive post-burn scar deformities, re-create the lost sub-dermal tissue, improvement in function of involved joint movements

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Authors: Lakmali Anthony, Bushra Oathman, Anshini Jain, Raaj Chandra

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Introduction: Abscesses are traditionally treated by incision and drainage with the packing of the residual abscess cavity until healing. This method requires regular visits from community nurses for continuous wound packing upon discharge from the hospital and causes considerable patient discomfort. Whether abscess cavity packing offers any advantage over non-packing has not yet been adequately studied to the best of our knowledge. This study aims to determine if there are differences in clinical outcomes of time to healing, fistula formation and recurrence of abscess between abscess cavity packing vs. non-packing groups. Methods: This study was a single-center, single-blind, randomized controlled trial where patients were randomized into packing and non-packing arms. All patients over 18 years presenting to Eastern Health with an abscess requiring incision and drainage in the theatre were invited to participate. Those with underlying conditions that cause recurrent abscesses were excluded. Data were collected from December 2018 to April 2020. Results: There were 63 patients who had abscesses treated with incision and drainage that were enrolled in the study, 52 of which were suitable for analysis. Demographic characteristics were similar in both groups. The packing group had a significantly longer time to heal compared to the non-packing group. Rates of fistula formation and recurrence of abscess were low and there were no statistically significant differences between groups. The packing group had more patients with delayed healing (defined as >60 days) and required more follow-up visits compared to the non-packing group. Conclusion: This pilot study indicates that abscesses can not only be managed safely with incision and drainage alone without the need for continuous abscess cavity packing but also that non-packing may offer clinical benefits to patients with earlier healing of abscesses compared to continuous cavity packing.

Keywords: abscess packing, subcutaneous, perianal, pilonidal

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Authors: Dawid Sołoducha, Tomasz Borowski, Agata Markowska-Szczupak, Aneta Wesołowska, Marian Kordas, Rafał Rakoczy

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Many studies report varied effects of the magnetic field in medicine, but applications are still missing. Also, essential oils (EOs) were historically used in healing therapies, food preservation and the cosmetic industry due to their wound healing and antioxidant properties and antimicrobial activity. Unfortunately, the chemical characterization of EOs activates its antibacterial action only at a fairly high concentration. They can cause skin reactions, e.g., irritation (irritant contact dermatitis) or allergic contact dermatitis; therefore, they should always be used with caution. However, the administration of EOs to achieve the desired antimicrobial activity and stability with long-term medical usage in low concentration is challenging. The aim of this work was to investigate the antimicrobial activity of commercial Pinus sylvestris L. essential oil from Polish company Avicenna-Oil® under Rotating Magnetic Field (RMF) at f = 1 – 50 Hz. The novel construction of the magnetically assisted self-constructed reactor (MAP) was applied for this study. The chemical composition of essential pine oil was determined by gas chromatography coupled with mass spectrometry (GC-MS). Model bacteria Escherichia coli K12 (ATCC 25922) was used. Different concentrations of pine oil was prepared: 100% 50%, 25%, 12.5% and 6.25%. The disc diffusion and MIC test were done. To examine the effect of essential pine oil and rotating magnetic field RMF on antibacterial performance agar plate method was used. Pine oil consist of α-pinene (28.58%), β-pinene (17.79%), δ-3-carene (14.17%) and limonene (11.58%). The present study indicates the exposition to the RMF, as compared to the unexposed controls causing an increase in the efficacy of antibacterial properties of pine oil. We have shown that the rotating magnetic fields (RMF) at a frequency, f, between 25 Hz to 50 Hz, increase the antimicrobial efficiency of oil at lower than 50% concentration. The new method can be applied in many fields e.g. aromatherapy, medicine as a component of dressing, or as food preservatives.

Keywords: rotating magnetic field, pine oil, antimicrobial activity, Escherichia coli

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Authors: Mounir Zekkaoui, Abdelhadi Fennan

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The software evolution control requires a deep understanding of the changes and their impact on different system heterogeneous artifacts. And an understanding of descriptive knowledge of the developed software artifacts is a prerequisite condition for the success of the evolutionary process. The implementation of an evolutionary process is to make changes more or less important to many heterogeneous software artifacts such as source code, analysis and design models, unit testing, XML deployment descriptors, user guides, and others. These changes can be a source of degradation in functional, qualitative or behavioral terms of modified software. Hence the need for a unified approach for extraction and representation of different heterogeneous artifacts in order to ensure a unified and detailed description of heterogeneous software artifacts, exploitable by several software tools and allowing to responsible for the evolution of carry out the reasoning change concerned.

Keywords: heterogeneous software artifacts, software evolution control, unified approach, meta model, software architecture

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Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

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Authors: Bruno T. Gomes, José A. Menezes, Giordano Cabral

Abstract:

With the popularity of smartphones, mobile apps emerge to meet the diverse needs, however the resources at the disposal are limited, either by the hardware, due to the low computing power, or the software, that does not have the same robustness of desktop environment. For example, in automatic audio classification (AC) tasks, musical information retrieval (MIR) subarea, is required a fast processing and a good success rate. However the mobile platform has limited computing power and the best AC tools are only available for desktop. To solve these problems the fast classifier suits, to mobile environments, the most widespread MIR technologies, seeking a balance in terms of speed and robustness. At the end we found that it is possible to enjoy the best of MIR for mobile environments. This paper presents the results obtained and the difficulties encountered.

Keywords: audio classification, audio extraction, environment mobile, musical information retrieval

Procedia PDF Downloads 541

Authors: Aiman Alshare, Sahar Qaadan

Abstract:

A curvature dependent force correction algorithm for planning force controlled grinding process with off-line programming flexibility is designed for ABB industrial robot, in order to avoid the manual interface during the process. The machining path utilizes a spline curve fit that is constructed from the CAD data of the workpiece. The fitted spline has a continuity of the second order to assure path smoothness. The implemented algorithm computes uniform forces normal to the grinding surface of the workpiece, by constructing a curvature path in the spatial coordinates using the spline method.

Keywords: ABB industrial robot, grinding process, offline programming, CAD data extraction, force correction algorithm

Procedia PDF Downloads 359