Search results for: fault propagation fold

Authors: Alaa A. Zaky, Bandar Alfaifi, Saleh Alyahya, Alkistis Kontou, Panos Kotsampopoulos

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In this work, we present for the first time the grid-integration of 3rd generation perovskite solar cells (PSCs) based on nanotechnology in fabrication. The effect of this penetration is analyzed in normal, fault and islanding cases of operation under different irradiation conditions using the power hardware in the loop (PHIL) methodology. The PHL method allows the PSCs connection to the electric grid which is simulated in the real-time digital simulator (RTDS), for laboratory validation of the PSCs behavior under conditions very close to real.

Keywords: perovskite solar cells, power hardware in the loop, real-time digital simulator, smart grid

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Authors: Shengyong Zhang, Mike Mikulich

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Vibration is a crucial limiting consideration in the analysis and design of airplane wing structures to avoid disastrous failures due to the propagation of existing cracks in the material. In this paper, we build CAD models of aircraft wings to capture the design intent with configurations. Subsequent FEA vibration analysis is performed to study the natural vibration properties and impulsive responses of the resulting user-defined wing models. This study reveals the variations of the wing’s vibration characteristics with respect to changes in its structural configurations. Integrating CAD modelling and FEA vibration analysis enables designers to improve wing architectures for implementing design requirements in the preliminary design stage.

Keywords: aircraft wing, CAD modelling, FEA, vibration analysis

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Authors: Preshanthan Moodley

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This study compares two different pretreatments for sugarcane leaf waste (SLW): steam salt-alkali (SSA) and microwave salt-alkali (MSA). The two pretreatment types were modelled, optimized, and validated with R² > 0.97. Reducing sugar yields of 1.21g/g were obtained with optimized SSA pretreatment using 1.73M ZnCl₂, 1.36M NaOH and 9.69% solid loading, and 1.17g/g with optimized MSA pretreatment using 1.67M ZnCl₂, 1.52M NaOH at 400W for 10min. A lower pretreatment time (10min) was required for the MSA model (83% lower). The structure of pretreated SLW was assessed using scanning electron microscopy (SEM) and Fourier Transform Infrared analysis (FTIR). The optimized SSA and MSA models showed lignin removal of 80.5 and 73% respectively. The MSA pretreatment was further examined on sorghum leaves and Napier grass and showed yield improvements of 1.9- and 2.8-fold compared to recent reports. The developed pretreatment methods demonstrated high efficiency at enhancing enzymatic hydrolysis on various lignocellulosic substrates.

Keywords: lignocellulosic biomass, pretreatment, salt, sugarcane leaves

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Authors: Yazan S. Khaled, Shazana Shamsuddin, Jim Tiernan, Mike McPherson, Thomas Hughes, Paul Millner, David G. Jayne

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Introduction: There is a need for real-time imaging of colorectal cancer (CRC) to allow tailored surgery to the disease stage. Fluorescence guided laparoscopic imaging of primary colorectal cancer and the draining lymphatics would potentially bring stratified surgery into clinical practice and realign future CRC management to the needs of patients. Fluorescent nanoparticles can offer many advantages in terms of intra-operative imaging and therapy (theranostic) in comparison with traditional soluble reagents. Nanoparticles can be functionalised with diverse reagents and then targeted to the correct tissue using an antibody or Affimer (artificial binding protein). We aimed to develop and test fluorescent silica nanoparticles and targeted against CRC using an anti-carcinoembryonic antigen (CEA) Affimer (Aff). Methods: Anti-CEA and control Myoglobin Affimer binders were subcloned into the expressing vector pET11 followed by transformation into BL21 Star™ (DE3) E.coli. The expression of Affimer binders was induced using 0.1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG). Cells were harvested, lysed and purified using nickle chelating affinity chromatography. The photosensitiser Foslip (soluble analogue of 5,10,15,20-Tetra(m-hydroxyphenyl) chlorin) was incorporated into the core of silica nanoparticles using water-in-oil microemulsion technique. Anti-CEA or control Affs were conjugated to silica nanoparticles surface using sulfosuccinimidyl-4-(N-maleimidomethyl) cyclohexane-1-carboxylate (sulfo SMCC) chemical linker. Binding of CEA-Aff or control nanoparticles to colorectal cancer cells (LoVo, LS174T and HC116) was quantified in vitro using confocal microscopy. Results: The molecular weights of the obtained band of Affimers were ~12.5KDa while the diameter of functionalised silica nanoparticles was ~80nm. CEA-Affimer targeted nanoparticles demonstrated 9.4, 5.8 and 2.5 fold greater fluorescence than control in, LoVo, LS174T and HCT116 cells respectively (p < 0.002) for the single slice analysis. A similar pattern of successful CEA-targeted fluorescence was observed in the maximum image projection analysis, with CEA-targeted nanoparticles demonstrating 4.1, 2.9 and 2.4 fold greater fluorescence than control particles in LoVo, LS174T, and HCT116 cells respectively (p < 0.0002). There was no significant difference in fluorescence for CEA-Affimer vs. CEA-Antibody targeted nanoparticles. Conclusion: We are the first to demonstrate that Foslip-doped silica nanoparticles conjugated to anti-CEA Affimers via SMCC allowed tumour cell-specific fluorescent targeting in vitro, and had shown sufficient promise to justify testing in an animal model of colorectal cancer. CEA-Affimer appears to be a suitable targeting molecule to replace CEA-Antibody. Targeted silica nanoparticles loaded with Foslip photosensitiser is now being optimised to drive photodynamic killing, via reactive oxygen generation.

Keywords: colorectal cancer, silica nanoparticles, Affimers, antibodies, imaging

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Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

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Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

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Authors: Shagil Akhtar, Syed Muneeb Iqbal, Mohammed R. Rahim

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Common steel tubes with similar confines were used in simulation of tubes with distinctive type of corrugated sections. These corrugated cross-sections were arc-tangent, triangular, trapezoidal and square corrugated sections. The outcome of fluctuating structures of tube cross-section shape on the deformation feedback, collapse form and energy absorption characteristics of tubes under quasi-static axial compression have been prepared numerically. The finite element package of ANSYS Workbench was applied in the current analysis. The axial load-displacement products accompanied by the fold formation of disparate tubes were inspected and compared. Deviation of the initial peak load and the mean crushing force of the tubes with distinctive cross-sections were conscientiously examined.

Keywords: absorbed energy, axial loading, corrugated tubes, finite element, initial peak load, mean crushing force

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Authors: Beth Jacobs

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The landmark movement of Western clinical psychology in the 20th century was the development of psychotherapy. The landmark movement of clinical psychology in the 21st century will be the absorption of meditation practices from Buddhist psychology. While millions of people explore meditation and related philosophy, very few people are exposed to the materials of original Buddhism on this topic, especially to the Theravadan Abhidharma. The Abhidharma is an intricate system of lists and matrixes that were used to understand and remember Buddha’s teaching. The Abhidharma delineates the first psychological system of Buddhism, how the mind works in the universe of reality and why meditation training strengthens and purifies the experience of life. Its lists outline the psychology of mental constructions, perception, emotion and cosmological causation. While the Abhidharma is technical, elaborate and complex, its essential purpose relates to the central purpose of clinical psychology: to relieve human suffering. Like Western depth psychology, the methodology rests on understanding underlying processes of consciousness and perception. What clinical psychologists might describe as therapeutic improvement, the Abhidharma delineates as a specific pathway of purified actions of consciousness. This paper discusses the concept of 'path' as presented in aspects of the Theravadan Abhidharma and relates this to current clinical psychological views of therapy outcomes and gains. The core path in Buddhism is the Eight-Fold Path, which is the fourth noble truth and the launching of activity toward liberation. The path is not composed of eight ordinal steps; it’s eight-fold and is described as opening the way, not funneling choices. The specific path in the Abhidharma is described in many steps of development of consciousness activities. The path is not something a human moves on, but something that moments of consciousness develop within. 'Cittas' are extensively described in the Abhidharma as the atomic-level unit of a raw action of consciousness touching upon an object in a field, and there are 121 types of cittas categorized. The cittas are embedded in the mental factors, which could be described as the psychological packaging elements of our experiences of consciousness. Based on these constellations of infinitesimal, linked occurrences of consciousness, citta are categorized by dimensions of purification. A path is a chain of citta developing through causes and conditions. There are no selves, no pronouns in the Abhidharma. Instead of me walking a path, this is about a person working with conditions to cultivate a stream of consciousness that is pure, immediate, direct and generous. The same effort, in very different terms, informs the work of most psychotherapies. Depth psychology seeks to release the bound, unconscious elements of mental process into the clarity of realization. Cognitive and behavioral psychologies work on breaking down automatic thought valuations and actions, changing schemas and interpersonal dynamics. Understanding how the original Buddhist concept of positive human development relates to the clinical psychological concept of therapy weaves together two brilliant systems of thought on the development of human well being.

Keywords: Abhidharma, Buddhist path, clinical psychology, psychotherapeutic outcome

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Authors: Yeshona Sewsynker

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This study presents three microwave-assisted alkalic salt pretreatments to enhance delignification and enzymatic saccharification of corn cobs. The effects of process parameters of salt concentration (0-15%), microwave power intensity (0-800 W) and pretreatment time (2-8 min) on reducing sugar yield from corn cobs were investigated. Pretreatment models were developed with the high coefficient of determination values (R2>0.85). Optimization gave a maximum reducing sugar yield of 0.76 g/g. Scanning electron microscopy (SEM) and Fourier Transform Infrared analysis (FTIR) showed major changes in the lignocellulosic structure after pretreatment. A 7-fold increase in the sugar yield was observed compared to previous reports on the same substrate. The developed pretreatment strategy was effective for enhancing enzymatic saccharification from lignocellulosic wastes for microbial biofuel production processes and value-added products.

Keywords: pretreatment, lignocellulosic biomass, enzymatic hydrolysis, delignification

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Authors: Hadi S. Hosseini, Larry A. Taber

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In the embryo, heart is initially a simple tubular structure that undergoes complex morphological changes as it transforms into a four-chambered pump. This work focuses on mechanisms that create heart tube (HT). The early embryo is composed of three relatively flat primary germ layers called endoderm, mesoderm, and ectoderm. Precardiac cells located within bilateral regions of the mesoderm called heart fields (HFs) fold and fuse along the embryonic midline to create the HT. The right and left halves of this plate fold symmetrically to bring their upper edges into contact along the midline, where they fuse. In a region near the fusion line, these layers then separate to generate the primitive HT and foregut, which then extend vertically. The anterior intestinal portal (AIP) is the opening at the caudal end of the foregut, which descends as the HT lengthens. The biomechanical mechanisms that drive this folding are poorly understood. Our central hypothesis is that folding is caused by differences in growth between the endoderm and mesoderm while subsequent extension is driven by contraction along the AIP. The feasibility of this hypothesis is examined using experiments with chick embryos and finite-element modeling (FEM). Fertilized white Leghorn chicken eggs were incubated for approximately 22-33 hours until appropriate Hamburger and Hamilton stage (HH5 to HH9) was reached. To inhibit contraction, embryos were cultured in media containing blebbistatin (myosin II inhibitor) for 18h. Three-dimensional models were created using ABAQUS (D. S. Simulia). The initial geometry consists of a flat plate including two layers representing the mesoderm and endoderm. Tissue was considered as a nonlinear elastic material with growth and contraction (negative growth) simulated using a theory, in which the total deformation gradient is given by F=F^*.G, where G is growth tensor and F* is the elastic deformation gradient tensor. In embryos exposed to blebbistatin, initial folding and AIP descension occurred normally. However, after HFs partially fused to create the upper part of the HT, fusion, and AIP descension stopped, and the HT failed to grow longer. These results suggest that cytoskeletal contraction is required only for the later stages of HT formation. In the model, a larger biaxial growth rate in the mesoderm compared to the endoderm causes the bilayered plate to bend ventrally, as the upper edge moves toward the midline, where it 'fuses' with the other half . This folding creates the upper section of the HT, as well as the foregut pocket bordered by the AIP. After this phase completes by stage HH7, contraction along the arch-shaped AIP pulls the lower edge of the plate downward, stretching the two layers. Results given by model are in reasonable agreement with experimental data for the shape of HT, as well as patterns of stress and strain. In conclusion, results of our study support our hypothesis for the creation of the heart tube.

Keywords: heart tube formation, FEM, chick embryo, biomechanics

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: Alam Ali, Ashok Kumar Pathak

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Path analysis is a statistical technique used to evaluate the strength of the direct and indirect effects of variables. One or more structural regression equations are used to estimate a series of parameters in order to find the better fit of data. Sometimes, exogenous variables do not show a significant strength of their direct and indirect effect when the assumption of classical regression (ordinary least squares (OLS)) are violated by the nature of the data. The main motive of this article is to investigate the efficacy of the copula-based regression approach over the classical regression approach and calculate the direct and indirect effects of variables when data violates the OLS assumption and variables are linked through an elliptical copula. We perform this study using a well-organized numerical scheme. Finally, a real data application is also presented to demonstrate the performance of the superiority of the copula approach.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

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Authors: Samira Cherid, Samir Bentata, F. Zahira Meghoufel, Sabria Terkhi, Yamina Sefir, Fatima Bendahma, Bouabdellah Bouadjemi, Ali Z. Itouni

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In this work, we examined the propagation of light in one-dimensional systems is examined by means of the random dimer model. The introduction of defect elements, randomly in the studied system, breaks down the Anderson localization and provides a set of propagating delocalized modes at the corresponding conventional dimer resonances. However, tuning suitably the defect dimer resonance on the host ones (or vice versa), the transmission magnitudes can be enhanced providing the optimized ballistic transmission regime as an average response. Hence, ballistic optical filters can be conceived at desired wavelengths.

Keywords: photonic crystals, random dimer model, ballistic resonance, localization and transmission

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Authors: Min Kyu Kim, Eun Young Lee, Dong Woo Son, Yoon Seok Chang

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In this paper, we introduce a flexible box erecting machine (BEM) that swiftly and automatically transforms cardboard into a three dimensional box. Recently, the parcel service and home-shopping industries have grown rapidly, and there is an increasing need for various box types to ship various products. However, workers cannot fold thousands of boxes manually in a day. As such, automatic BEMs are garnering greater attention. This study takes equipment operation into consideration as well as mechanical improvements in order to design a BEM that is able to outperform its conventional counterparts. We analyzed six dispatching rules – First In First Out (FIFO), Shortest Processing Time (SPT), Earliest Due Date (EDD), Setup Avoidance, EDD + SPT, and EDD + Setup Avoidance – to determine which one was most suitable for BEM operation. Consequently, SPT and Setup Avoidance were found to be the most critical rules, followed by EDD + Setup Avoidance, EDD + SPT, EDD, and FIFO. This hierarchy was valid for both our conventional BEM and our new flexible BEM from the viewpoint of processing time. We believe that this research can contribute to flexible BEM management, which has the potential to increase productivity and convenience.

Keywords: automation, box erecting machine, dispatching rule, setup time

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Authors: Tomas Makaras, Julija Razumienė, Vidutė Gurevičienė, Gintarė Sauliutė, Milda Stankevičiūtė

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Stress responses represent animal’s natural reactions to various challenging conditions and could be used as a welfare indicator. Regardless of the wide use of glucose measurements in stress evaluation, there are some inconsistencies in its acceptance as a stress marker, especially when it comes to comparison with non-invasive cortisol measurements in the fish challenging stress. To meet the challenge and to test the reliability and applicability of glucose measurement in practice, in this study, different environmental/anthropogenic exposure scenarios were simulated to provoke chemical-induced stress in fish (14-days exposure to landfill leachate) followed by a 14-days stress recovery period and under the cumulative effect of leachate fish subsequently exposed to pathogenic oomycetes (Saprolegnia parasitica) to represent a possible infection in fish. It is endemic to all freshwater habitats worldwide and is partly responsible for the decline of natural freshwater fish populations. Brown trout (Salmo trutta fario) and sea trout (Salmo trutta trutta) juveniles were chosen because of a large amount of literature on physiological stress responses in these species was known. Glucose content in fish by applying invasive and non-invasive glucose measurement procedures in different test mediums such as fish blood, gill tissues and fish-holding water were analysed. The results indicated that the quantity of glucose released in the holding water of stressed fish increased considerably (approx. 3.5- to 8-fold) and remained substantially higher (approx. 2- to 4-fold) throughout the stress recovery period than the control level suggesting that fish did not recover from chemical-induced stress. The circulating levels of glucose in blood and gills decreased over time in fish exposed to different stressors. However, the gill glucose level in fish showed a decrease similar to the control levels measured at the same time points, which was found to be insignificant. The data analysis showed that concentrations of β-D glucose measured in gills of fish treated with S. parasitica differed significantly from the control recovery, but did not differ from the leachate recovery group showing that S. parasitica presence in water had no additive effects. In contrast, a positive correlation between blood and gills glucose were determined. Parallel trends in blood and water glucose changes suggest that water glucose measurement has much potency in predicting stress. This study demonstrated that measuring β-D-glucose in fish-holding water is not stressful as it involves no handling and manipulation of an organism and has critical technical advantages concerning current (invasive) methods, mainly using blood samples or specific tissues. The quantification of glucose could be essential for studies examining the stress physiology/aquaculture studies interested in the assessment or long-term monitoring of fish health.

Keywords: brown trout, landfill leachate, sea trout, pathogenic oomycetes, β-D-glucose

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Authors: M. Sasajima, T. Yamaguchi, Y. Hu, Y. Koike

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In this paper, we discuss the propagation of sound in the narrow pathways of an occluded-ear simulator typically used for the measurement of insert-type earphones. The simulator has a standardized frequency response conforming to the international standard (IEC60318-4). In narrow pathways, the speed and phase of sound waves are modified by viscous air damping. In our previous paper, we proposed a new finite element method (FEM) to consider the effects of air viscosity in this type of audio equipment. In this study, we will compare the results from the ear simulator FEM model, and those from a three dimensional human ear canal FEM model made from computed tomography images, with the measured frequency response data from the ear canals of 18 people.

Keywords: ear simulator, FEM, viscosity, human ear canal

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Authors: Sahira N. Muslim, Alaa N. Mohammed, Saba Saadoon Khazaal, Batool Kadham Salman, Israa M. S. AL-Kadmy, Sraa N. Muslim, Ahmed S. Dwaish, Sawsan Mohammed Kareem, Sarah N. Aziz, Ruaa A. Jasim

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Tannase has wide applications in food, beverage, brewing, cosmetics and chemical industries and one of the major applications of tannase is the production of gallic acid. Gallic acid is used for manufacturing of trimethoprim. In the present study, a local fungal strain of Penicillium expansum A₄ isolated from spoilt apple samples gave the highest production level of tannase. Tannase was partially purified with a recovery yield of 92.52% and 6.32 fold of purification by precipitation using ammonium sulfate at 50% saturation. Tannase led to increased antimicrobial activity of ceftazidime against Pseudomonas aeruginosa and S. aureus and had a synergism effect at low concentrations of ceftazidime, and thus, tannase may be a useful adjuvant agent for the treatment of many bacterial infections in combination with ceftazidime.

Keywords: ceftazidime, Penicillium expansum, tannase, antimicrobial activity

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Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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Authors: A. Basu, A. A. Purohit, M. M. Vaidya, M. D. Kudale

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Mumbai, being traditionally the epicenter of India's trade and commerce, the existing major ports such as Mumbai and Jawaharlal Nehru Ports (JN) situated in Thane estuary are also developing its waterfront facilities. Various developments over the passage of decades in this region have changed the tidal flux entering/leaving the estuary. The intake at Pir-Pau is facing the problem of shortage of water in view of advancement of shoreline, while jetty near Ulwe faces the problem of ship scheduling due to existence of shallower depths between JN Port and Ulwe Bunder. In order to solve these problems, it is inevitable to have information about tide levels over a long duration by field measurements. However, field measurement is a tedious and costly affair; application of artificial intelligence was used to predict water levels by training the network for the measured tide data for one lunar tidal cycle. The application of two layered feed forward Artificial Neural Network (ANN) with back-propagation training algorithms such as Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to predict the yearly tide levels at waterfront structures namely at Ulwe Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe, and Vashi for a period of lunar tidal cycle (2013) was used to train, validate and test the neural networks. These trained networks having high co-relation coefficients (R= 0.998) were used to predict the tide at Ulwe, and Vashi for its verification with the measured tide for the year 2000 & 2013. The results indicate that the predicted tide levels by ANN give reasonably accurate estimation of tide. Hence, the trained network is used to predict the yearly tide data (2015) for Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was predicted by using the neural network which was trained with the help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is maximum amplification of tide by about 10-20 cm with a phase lag of 10-20 minutes with reference to the tide at Apollo Bunder (Mumbai). LM training algorithm is faster than GD and with increase in number of neurons in hidden layer and the performance of the network increases. The predicted tide levels by ANN at Pir-Pau and Ulwe provides valuable information about the occurrence of high and low water levels to plan the operation of pumping at Pir-Pau and improve ship schedule at Ulwe.

Keywords: artificial neural network, back-propagation, tide data, training algorithm

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Authors: Muhammad Asghar Saqib, Saad Saleem Khan, Syed Abdul Rahman Kashif

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In order to have higher efficiency, performance and reliability the regular monitoring of an electrical motor is required. This article presents a novel view of the air-gap magnetic field analysis of a switched reluctance motor under rotor cracks and rotor tilt along its shaft axis. The fault diagnosis is illustrated on the basis of a 3-D model of the motor using finite element analysis (FEA). The analytical equations of flux linkages have been used to determine the inductance. The results of the 3-D finite element analysis on a 6/4 switched reluctance motor (SRM) shows the variation of mutual inductance with the tilting of the rotor shaft and cracked rotor conditions. These results present useful information regarding the detection of shaft tilting and cracked rotors.

Keywords: switched reluctance motor, finite element analysis, cracked rotor, 3-D modelling of a srm

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Authors: K. S. Al-Mugren, A. Yahya, S. Alodah, R. Alharbi, S. H. Almsaid , A. Alqahtani, H. Jaber, A. Basaqer, N. Alajra, N. Almoghati, A. Alsalman, Khalid Alharbi

Abstract:

Context: The production of biofertilizers from naturally occurring microorganisms is an area of research that aims to enhance agricultural practices by utilizing local resources. This research project focuses on isolating and screening indigenous microorganisms with PK-fixing and phosphate solubilizing characteristics from local sources. Research Aim: The aim of this project is to develop a biofertilizer product using indigenous microorganisms and composted agro waste as a carrier. The objective is to enhance crop productivity and soil fertility through the application of biofertilizers. Methodology: The research methodology includes several key steps. Firstly, indigenous microorganisms will be isolated from local resources using the ten-fold serial dilutions technique. Screening assays will be conducted to identify microorganisms with phosphate solubilizing and PK-fixing activities. Agro-waste materials will be collected from local agricultural sources, and composting experiments will be conducted to convert them into organic matter-rich compost. Physicochemical analysis will be performed to assess the composition of the composted agro-waste. Gamma and X-ray irradiation will be used to sterilize the carrier material. The sterilized carrier will be tested for sterility using the ten-fold serial dilutions technique. Finally, selected indigenous microorganisms will be developed into biofertilizer products. Findings: The research aims to find suitable indigenous microorganisms with phosphate solubilizing and PK-fixing characteristics for biofertilizer production. Additionally, the research aims to assess the suitability of composted agro waste as a carrier for biofertilizers. The impact of gamma irradiation sterilization on pathogen elimination will also be investigated. Theoretical Importance: This research contributes to the understanding of utilizing indigenous microorganisms and composted agro waste for biofertilizer production. It expands knowledge on the potential benefits of biofertilizers in enhancing crop productivity and soil fertility. Data Collection and Analysis Procedures: The data collection process involves isolating indigenous microorganisms, conducting screening assays, collecting and composting agro waste, analyzing the physicochemical composition of composted agro waste, and testing carrier sterilization. The analysis procedures include assessing the abilities of indigenous microorganisms, evaluating the composition of composted agro waste, and determining the sterility of the carrier material. Conclusion: The research project aims to develop biofertilizer products using indigenous microorganisms and composted agro waste as a carrier. Through the isolation and screening of indigenous microorganisms, the project aims to enhance crop productivity and soil fertility by utilizing local resources. The research findings will contribute to the understanding of the suitability of composted agro waste as a carrier and the efficacy of gamma irradiation sterilization. The research outcomes will have theoretical importance in the field of biofertilizer production and agricultural practices.

Keywords: biofertilizer, microorganisms, agro waste, nuclear technologies

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Authors: Yi-Hua Chen, Hsiang-Wen Tang, I-Ling Chang, Lien-Wen Chen

Abstract:

The defect mode of two-dimensional phononic crystals with Archimedean tilings was explored in the present study. Finite element method and supercell method were used to obtain dispersion relation of phononic crystals. The simulations of the acoustic wave propagation within phononic crystals are demonstrated. Around the cavity which is created by removing several cylinders in the perfect Archimedean tilings, whispering-gallery mode (WGM) can be observed. The effects of the cavity geometry on the WGM modes are investigated. The WGM modes with high Q-factor and high cavity pressure can be obtained by phononic crystals with Archimedean tilings.

Keywords: defect mode, Archimedean tilings, phononic crystals, whispering-gallery modes

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Authors: Oluwaponmile David Alao

Abstract:

Misdiagnosis has been the major problem in health sector. Heart attack has been one of diseases that have high level of misdiagnosis recorded on the part of physicians. In this paper, an intelligent system has been developed for diagnosis of heart attack in the health sector. Dataset of heart attack obtained from UCI repository has been used. This dataset is made up of thirteen attributes which are very vital in diagnosis of heart disease. The system is developed on the multilayer perceptron trained with back propagation neural network then simulated with feed forward neural network and a recognition rate of 87% was obtained which is a good result for diagnosis of heart attack in medical field.

Keywords: heart attack, artificial neural network, diagnosis, intelligent system

Procedia PDF Downloads 653

Authors: Raphael Rehmet, Armin Lohrengel, Prof Dr-Ing

Abstract:

In terms of making machines more silent and convenient, it is necessary to analyze the transmission path of mechanical vibrations and structure-bone noise. A typical solution for the elimination of structure-bone noise would be to simply add stiffeners or additional masses to change the transmission behavior and, thereby, avoid the propagation of vibrations. Another solution could be to use materials with a different damping behavior, such as elastomers, to isolate the machine dynamically. This research approach investigates the damping behavior of additive printed components made from structural steel or titanium, which have been manufactured in the “Laser Powder Bed Fusion“-process. By using the design flexibility which this process comes with, it will be investigated how a local impedance difference will affect the transmission behavior of the specimens.

Keywords: 3D-printed, acoustics, dynamics, impedance

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Authors: Sunil Kamboj, Suman Bala, Vipin Saini

Abstract:

Niosomes were formulated with an aim of enhancing the oral bioavailability of losartan potassium and formulated in different molar ratios of surfactant, cholesterol and dicetyl phosphate. The formulated niosomes were found in range of 54.98 µm to 107.85 µm in size. Formulations with 1:1 ratio of surfactant and cholesterol have shown maximum entrapment efficiencies. Niosomes with sorbitan monostearate showed maximum drug release and zero order release kinetics, at the end of 24 hours. The in vivo study has shown the significant enhancement in oral bioavailability of losartan potassium in rats, after a dose of 10 mg/kg. The average relative bioavailability in relation with pure drug solution was found 2.56, indicates more than two fold increase in oral bioavailability. A significant increment in MRT reflects the release retarding ability of the vesicles. In conclusion, niosomes could be a promising delivery of losartan potassium with improved oral bioavailability and prolonged release profiles.

Keywords: non-ionic surfactant vesicles, losartan potassium, oral bioavailability, controlled release

Procedia PDF Downloads 352

Authors: B. Tiseo, V. Quaranta, G. Bruno, R. Gardi, T. Watts, S. Dussy

Abstract:

This paper describes the qualification test campaign performed on the Demise Observation Capsule DOC-EQM as part of the Future Launch Preparatory Program FLPP3. The mechanical environment experienced during launch ascent and separation phase was first identified and then replicated in terms of sine, random and shock vibration. The loads identification is derived by selecting the worst possible case. Vibration and shock qualification test performed at CIRA Space Qualification laboratory is herein described. Mechanical fixtures’ design and validation, carried out by means of FEM, is also addressed due to its fundamental role in the vibrational test campaign. The Demise Observation Capsule (DOC) successfully passed the qualification test campaign. Functional test and resonance search have not been point any fault and damages of the capsule.

Keywords: capsule, demise, demise observation capsule, DOC, launch environment, re-ntry, qualification

Procedia PDF Downloads 150

Authors: E. Popov, N. Yorino, Y. Zoka, Y. Sasaki, H. Sugihara

Abstract:

This paper discusses the performance of critical trajectory method (CTrj) for power system transient stability analysis under various loading settings and heavy fault condition. The method obtains Controlling Unstable Equilibrium Point (CUEP) which is essential for estimation of power system stability margins. The CUEP is computed by applying the CTrjto the boundary controlling unstable equilibrium point (BCU) method. The Proposed method computes a trajectory on the stability boundary that starts from the exit point and reaches CUEP under certain assumptions. The robustness and effectiveness of the method are demonstrated via six power system models and five loading conditions. As benchmark is used conventional simulation method whereas the performance is compared with and BCU Shadowing method.

Keywords: power system, transient stability, critical trajectory method, energy function method

Procedia PDF Downloads 384

Authors: Dini Dewi Heniarti

Abstract:

This One of criminal sanctions that are often imposed by the judge is imprisonment. The issue on the imposition of imprisonment has been subject of contentious debate and criticism among various groups for a long time. In practice, the problematics of imprisonment lead to complicated problems. The impact of the reckless imposition of the imprisonment includes among others overcapacity of the correctional institution and increasing crimes within the correctional facilities. Therefore, there is a need for renewal of the existing condemnation paradigm, considering the developing phenomena associated with the penal imposition. Imprisonment as one element of the Indonesian penal system is an important and integral part of the other elements. The philosophy of the current penal system, which still refers to the Criminal Code, still carries the values of retaliation and fault-finding toward the offender. Therefore, it is important to reconstruct a new thought in order to realize a penal system that is represented in the formulation of a more humanistic criminal sanction

Keywords: criminal code, criminal sanction, Indonesian legal system, reconstruction of thought

Procedia PDF Downloads 224

Authors: Miroslav Gutten, Daniel Korenciak, Milan Simko, Milan Chupac

Abstract:

Ensure the reliable and correct function of transformers is the main essence of on-line non-destructive diagnostic tool, which allows the accurately track of the status parameters. Devices for on-line diagnostics are very costly. However, there are devices, whose price is relatively low and when used correctly, they can be executed a complex diagnostics. One of these devices is sensor HYDRAN M2, which is used to detect the moisture and gas content in the insulation oil. Using the sensor HYDRAN M2 in combination with temperature, load measurement, and physicochemical analysis can be made the economically inexpensive diagnostic system, which use is not restricted to distribution transformers. This system was tested in educational laboratory environment at measured oil transformer 22/0.4 kV. From the conclusions referred in article is possible to determine, which kind of fault was occurred in the transformer and how was an impact on the temperature, evolution of gases and water content.

Keywords: transformer, diagnostics, gas and moisture sensor, monitoring

Procedia PDF Downloads 383

Authors: R. Borghol, T. Aguili

Abstract:

In this paper, we investigate theoretically the waves propagation in a lossless double-negative grounded slab (DNG). This study is performed by the Transverse Resonance Method (TRM). The proper or improper nature of real and complex modes is observed. They are highly dependent on metamaterial parameters, i.e. ɛ_r-negative, µ_r-negative, or both. Numerical results provided that only the proper complex modes (i.e., leaky modes) exist in DNG slab, and only the improper complex modes exist in single-negative grounded slab.

Keywords: double negative grounded slab, real and complex modes, single negative grounded slab, transverse resonance method

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Authors: Mahdi Bazarganigilani

Abstract:

Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

Procedia PDF Downloads 160