Search results for: prediction of publications

Authors: Ayoub Bouazza, Ali Faddouli, Said Amal, Rachid Benhida, Khaoula Khaless

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Brine waste generated from reverse osmosis (RO) desalination plants contains various valuable compounds, mainly salts, trace elements, and organic matter. These wastes are up to two times saltier than standard seawater. Therefore, there is a strong economic interest in recovering these salts. The current practice in desalination plants is to reject the brine back to the sea, which affects the marine ecosystem and the environment. Our study aims to bring forth a reliable management solution for the valorisation of waste brines. Natural evaporation, isothermal evaporation at 25°C and 50°C, and evaporation using continuous heating were used to crystallize valuable salts from a reverse osmosis desalination plant brine located on the Moroccan Atlantic coast. The crystallization sequence of the brine was studied in comparison with standard seawater. The X-Ray Diffraction (XRD) of the precipitated solid phases showed similar results, where halite was the main solid phase precipitated from both the brine and seawater. However, Jänecke diagram prediction, along with FREZCHEM simulations, showed that Kainite should crystallize before Epsomite and Carnallite. As the absence of kainite formation in many experiments in the literature has been related to the metastability of kainite and the critical relative humidity conditions, and the precipitation of K–Mg salts is very sensitive to climatic conditions. An evaporation process is proposed as a solution to achieve the predicted crystallization path and to affirm the recovery of Kainite.

Keywords: salts crystallization, reverse osmosis, solar evaporation, frezchem, ZLD

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Authors: Oyesoji Aremu, Taiwo Williams

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This study examined some factors (academic self-efficacy, locus of control, motivation and gender) that could predict academic dishonesty among serially frustrated students in Ogun State, South West, Nigeria. Serial academically frustrated students are students who are unable to attain and meet academic expectations set by themselves or significant others. A sample of 250 undergraduate students selected from two faculties from a University in Ogun State,South West Nigeria took part in the study. Multiple regression analysis was employed to determine the joint and relative contributions of the independent variables to the prediction of the dependent variable. T-test was used to test the hypothesis determining the gender difference between the independent variables (academic self-efficacy, locus of control and motivation) and academic dishonesty of serial academically frustrated male and female students. The results of the study showed all the independent variables jointly contributed to predicting academic dishonesty, while only academic self-efficacy and motivation had relative contributions to the dependent measure. There was no significant difference in the academic self-efficacy and motivation among males and females on academic dishonesty of the serial academically frustrated students but locus of control showed a significant difference between male and female students on academic dishonesty. Implications for counseling of the findings are discussed in the study.

Keywords: academic dishonesty, serially frustrated students, academic self-efficacy, locus of control

Procedia PDF Downloads 254

Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Anurag Niranjan, Michael Fitzpatrick, Yin Jin Janin, Jazeel Chukkan, Niall Smyth

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Fillet welds are used in joining longitudinal stiffeners in ship structures. Welding residual stresses in fillet welds are generally distributed in a non-uniform manner, as shown in previous research the residual stress redistribution occurs under the cyclic loading that is experienced by such joints during service, and the combination of the initial residual stress, local constraints, and loading can alter the stress field in ways that are extremely difficult to predict. As the residual stress influences the crack propagation originating from the toe of the fillet welds, full understanding of the residual stress field and how it evolves is very important for structural integrity calculations. Knowledge of the residual stress redistribution in the presence of a flaw is therefore required for better fatigue life prediction. Moreover, defect assessment procedures such as BS7910 offer very limited guidance for flaw acceptance and the associated residual stress redistribution in the assessment of fillet welds. Therefore the objective of this work is to study a surface-breaking flaw at the weld toe region in a fillet weld under cyclic load, in conjunction with residual stress measurement at pre-defined crack depths. This work will provide details of residual stress redistribution under cyclic load in the presence of a crack. The outcome of this project will inform integrity assessment with respect to the treatment of residual stress in fillet welds. Knowledge of the residual stress evolution for this weld geometry will be greatly beneficial for flaw tolerance assessments (BS 7910, API 591).

Keywords: fillet weld, fatigue, residual stress, structure integrity

Procedia PDF Downloads 142

Authors: Meysam Naeimi, Zili Li, Roumen Petrov, Rolf Dollevoet, Jilt Sietsma, Jun Wu

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The substantial similarity of fatigue mechanism in a new test rig for rolling contact fatigue (RCF) has been investigated. A new reduced-scale test rig is designed to perform controlled RCF tests in wheel-rail materials. The fatigue mechanism of the rig is evaluated in this study using a combined finite element-fatigue prediction approach. The influences of loading conditions on fatigue crack initiation have been studied. Furthermore, the effects of some artificial defects (squat-shape) on fatigue lives are examined. To simulate the vehicle-track interaction by means of the test rig, a three-dimensional finite element (FE) model is built up. The nonlinear material behaviour of the rail steel is modelled in the contact interface. The results of FE simulations are combined with the critical plane concept to determine the material points with the greatest possibility of fatigue failure. Based on the stress-strain responses, by employing of previously postulated criteria for fatigue crack initiation (plastic shakedown and ratchetting), fatigue life analysis is carried out. The results are reported for various loading conditions and different defect sizes. Afterward, the cyclic mechanism of the test rig is evaluated from the operational viewpoint. The results of fatigue life predictions are compared with the expected number of cycles of the test rig by its cyclic nature. Finally, the estimative duration of the experiments until fatigue crack initiation is roughly determined.

Keywords: fatigue, test rig, crack initiation, life, rail, squats

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Authors: Adeniyi G. Adeogun, Bolaji F. Sule, Adebayo W. Salami, Michael O. Daramola

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Estimation of water yield and water balance in a river catchment is critical to the sustainable management of water resources at watershed level in any country. Therefore, in the present study, Soil and Water Assessment Tool (SWAT) interfaced with Geographical Information System (GIS) was applied as a tool to predict water balance and water yield of a catchment area in Nigeria. The catchment area, which was 12,992km2, is located upstream Jebba hydropower dam in North central part of Nigeria. In this study, data on the observed flow were collected and compared with simulated flow using SWAT. The correlation between the two data sets was evaluated using statistical measures, such as, Nasch-Sucliffe Efficiency (NSE) and coefficient of determination (R2). The model output shows a good agreement between the observed flow and simulated flow as indicated by NSE and R2, which were greater than 0.7 for both calibration and validation period. A total of 42,733 mm of water was predicted by the calibrated model as the water yield potential of the basin for a simulation period 1985 to 2010. This interesting performance obtained with SWAT model suggests that SWAT model could be a promising tool to predict water balance and water yield in sustainable management of water resources. In addition, SWAT could be applied to other water resources in other basins in Nigeria as a decision support tool for sustainable water management in Nigeria.

Keywords: GIS, modeling, sensitivity analysis, SWAT, water yield, watershed level

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Authors: Upasana Bhumbla

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Background: Hepatitis C virus is a major cause of chronic hepatitis, which can further lead to cirrhosis of the liver and hepatocellular carcinoma. Worldwide the burden of Hepatitis C infection has become a serious threat to the human race. Hepatitis C virus (HCV) has population-specific genotypes and provides valuable epidemiological and therapeutic information. Genotyping and assessment of viral load in HCV patients are important for planning the therapeutic strategies. The aim of the study is to study the changing trends of prevalence and genotypic distribution of hepatitis C virus in a tertiary care hospital in Western India. Methods: It is a retrospective study; blood samples were collected and tested for anti HCV antibodies by ELISA in Dept. of Microbiology. In seropositive Hepatitis C patients, quantification of HCV-RNA was done by real-time PCR and in HCV-RNA positive samples, genotyping was conducted. Results: A total of 114 patients who were seropositive for Anti HCV were recruited in the study, out of which 79 (69.29%) were HCV-RNA positive. Out of these positive samples, 54 were further subjected to genotype determination using real-time PCR. Genotype was not detected in 24 samples due to low viral load; 30 samples were positive for genotype. Conclusion: Knowledge of genotype is crucial for the management of HCV infection and prediction of prognosis. Patients infected with HCV genotype 1 and 4 will have to receive Interferon and Ribavirin for 48 weeks. Patients with these genotypes show a poor sustained viral response when tested 24 weeks after completion of therapy. On the contrary, patients infected with HCV genotype 2 and 3 are reported to have a better response to therapy.

Keywords: hepatocellular, genotype, ribavarin, seropositive

Procedia PDF Downloads 127

Authors: Assel Thami Lahlou, Soufiane Stouti, Ismail Lagrat, Hamid Mounir, Oussama Bouazaoui

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The purpose of this research work is to predict the helicopter from stalling by finding the minimum and maximum values that the pitch angle can take in order to fly in a hover state condition. The stall of a helicopter in hover occurs when the pitch angle is too small to generate the thrust required to support its weight or when the critical angle of attack that gives maximum lift is reached or exceeded. In order to find the minimum pitch angle, a 3D CFD simulation was done in this work using ANSYS FLUENT as the CFD solver. We started with a small value of the pitch angle θ, and we kept increasing its value until we found the thrust coefficient required to fly in a hover state and support the weight of the helicopter. For the CFD analysis, the Multiple Reference Frame (MRF) method with k-ε turbulent model was used to study the 3D flow around the rotor for θmin. On the other hand, a 2D simulation of the airfoil NACA 0012 was executed with a velocity inlet Vin=ΩR/2 to visualize the flow at the location span R/2 of the disk rotor using the Spallart-Allmaras turbulent model. Finding the critical angle of attack at this position will give us the ability to predict the stall in hover flight. The results obtained will be exposed later in the article. This study was so useful in analyzing the limitations of the helicopter’s main rotor and thus, in predicting accidents that can lead to a lot of damage.

Keywords: aerodynamic, CFD, helicopter, stall, blades, main rotor, minimum pitch angle, maximum pitch angle

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Authors: Filipa Cortez, Vanessa Pereira

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Introduction: The main challenge of obesity treatment is long-term weight loss maintenance. The 3 phases method is a weight loss program that combines a low carb and moderately high-protein diet, food supplements and a weekly one-to-one consultation with a certified nutritionist. Sustained weight control is the ultimate goal of phase 3. Success criterion was the minimum loss of 10% of initial weight and its maintenance after 12 months. Objective: The aim of this study was to identify factors associated with successful weight loss maintenance after 12 months at the end of 3 phases method. Methods: The study included 199 subjects that achieved their weight loss goal (phase 3). Weight and body mass index (BMI) were obtained at the baseline and every week until the end of the program. Therapeutic adherence was measured weekly on a Likert scale from 1 to 5. Subjects were considered in compliance with nutritional recommendation and supplementation when their classification was ≥ 4. After 12 months of the method, the current weight and number of previous weight-loss attempts were collected by telephone interview. The statistical significance was assumed at p-values < 0.05. Statistical analyses were performed using SPSS TM software v.21. Results: 65.3% of subjects met the success criterion. The factors which displayed a significant weight loss maintenance prediction were: greater initial percentage weight loss (OR=1.44) during the weight loss intervention and a higher number of consultations in phase 3 (OR=1.10). Conclusion: These findings suggest that the percentage weight loss during the weight loss intervention and the number of consultations in phase 3 may facilitate maintenance of weight loss after the 3 phases method.

Keywords: obesity, weight maintenance, low-carbohydrate diet, dietary supplements

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Andrej Golowin, Viktor Denk, Axel Riepe

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Solid fan blades and discs in aero engines are subjected to high combined low and high cycle fatigue loads especially around the contact areas between blade and disc. Therefore, special coatings (e.g. dry film lubricant) and surface treatments (e.g. shot peening or laser shock peening) are applied to increase the strength with respect to combined cyclic fatigue and fretting fatigue, but also to improve damage tolerance capability. The traditional deterministic damage tolerance assessment based on fracture mechanics analysis, which treats service damage as an initial crack, often gives overly conservative results especially in the presence of vibratory stresses. A probabilistic damage tolerance methodology using crack initiation data has been developed for fan discs exposed to relatively high vibratory stresses in cross- and tail-wind conditions at certain resonance speeds for limited time periods. This Monte-Carlo based method uses a damage databank from similar designs, measured vibration levels at typical aircraft operations and wind conditions and experimental crack initiation data derived from testing of artificially damaged specimens with representative surface treatment under combined fatigue conditions. The proposed methodology leads to a more realistic prediction of the minimum damage tolerance life for the most critical locations applicable to modern fan disc designs.

Keywords: combined fatigue, damage tolerance, engine, surface treatment

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Authors: Shohreh Ghasemi

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Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

Procedia PDF Downloads 81

Authors: Haruna Maama

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Environmental, social and governance (ESG) reporting is gaining considerable attention despite being voluntary. Meanwhile, it consumes resources to provide ESG reporting, raising a question of its value relevance. The study examined the impact of ESG reporting on the market value of listed firms in SSA. The annual and integrated reports of 276 listed sub-Sahara Africa (SSA) firms. The integrated reporting scores of the firm were analysed using a content analysis method. A multiple regression estimation technique using a GMM approach was employed for the analysis. The results revealed that ESG has a positive relationship with firms’ market value, suggesting that investors are interested in the ESG information disclosure of firms in SSA. This suggests that extensive ESG disclosures are attempts by firms to obtain the approval of powerful social, political and environmental stakeholders, especially institutional investors. Furthermore, the market value analysis evidence is consistent with signalling theory, which postulates that firms provide integrated reports as a signal to influence the behaviour of stakeholders. This finding reflects the value placed on investors' social, environmental and governance disclosures, which affirms the views that conventional investors would care about the social, environmental and governance issues of their potential or existing investee firms. Overall, the evidence is consistent with the prediction of signalling theory. In the context of this theory, integrated reporting is seen as part of firms' overall competitive strategy to influence investors' behaviour. The findings of this study make unique contributions to knowledge and practice in corporate reporting.

Keywords: environmental accounting, ESG accounting, signalling theory, sustainability reporting, sub-saharan Africa

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Authors: J. P. Panda, K. Sasmal, H. V. Warrior

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Eddy viscosity models in turbulence modeling can be mainly classified as linear and nonlinear models. Linear formulations are simple and require less computational resources but have the disadvantage that they cannot predict actual flow pattern in complex geophysical flows where streamline curvature and swirling motion are predominant. A constitutive equation of Reynolds stress anisotropy is adopted for the formulation of eddy viscosity including all the possible higher order terms quadratic in the mean velocity gradients, and a simplified model is developed for actual oceanic flows where only the vertical velocity gradients are important. The new model is incorporated into the one dimensional General Ocean Turbulence Model (GOTM). Two realistic oceanic test cases (OWS Papa and FLEX' 76) have been investigated. The new model predictions match well with the observational data and are better in comparison to the predictions of the two equation k-epsilon model. The proposed model can be easily incorporated in the three dimensional Princeton Ocean Model (POM) to simulate a wide range of oceanic processes. Practically, this model can be implemented in the coastal regions where trasverse shear induces higher vorticity, and for prediction of flow in estuaries and lakes, where depth is comparatively less. The model predictions of marine turbulence and other related data (e.g. Sea surface temperature, Surface heat flux and vertical temperature profile) can be utilized in short term ocean and climate forecasting and warning systems.

Keywords: Eddy viscosity, turbulence modeling, GOTM, CFD

Procedia PDF Downloads 202

Authors: Y. Mehdipour, S. Ebrahimi, A. Jahanpour, F. Seyedzaei, B. Sabayan, A. Karimi, H. Amirifard

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Ischemic stroke is one of the common reasons for disability and mortality. The fourth leading cause of death in the world and the third in some other sources. Only 1/3 of the patients with ischemic stroke fully recover, 1/3 of them end in permanent disability and 1/3 face death. Thus, the use of predictive models to predict stroke has a vital role in reducing the complications and costs related to this disease. Thus, the aim of this study was to specify the effective factors and predict ischemic stroke with the help of DM methods. The present study was a descriptive-analytic study. The population was 213 cases from among patients referring to Ali ibn Abi Talib (AS) Hospital in Zahedan. Data collection tool was a checklist with the validity and reliability confirmed. This study used DM algorithms of decision tree for modeling. Data analysis was performed using SPSS-19 and SPSS Modeler 14.2. The results of the comparison of algorithms showed that CHAID algorithm with 95.7% accuracy has the best performance. Moreover, based on the model created, factors such as anemia, diabetes mellitus, hyperlipidemia, transient ischemic attacks, coronary artery disease, and atherosclerosis are the most effective factors in stroke. Decision tree algorithms, especially CHAID algorithm, have acceptable precision and predictive ability to determine the factors affecting ischemic stroke. Thus, by creating predictive models through this algorithm, will play a significant role in decreasing the mortality and disability caused by ischemic stroke.

Keywords: data mining, ischemic stroke, decision tree, Bayesian network

Procedia PDF Downloads 175

Authors: Yungtai Lo

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Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-log-normal random effects model, a two-part logit-truncated normal random effects model, a two-part logit-gamma random effects model, and a two-part logit-skew normal random effects model were used to examine effects of a bottle-weaning intervention on reducing bottle use and daily milk intake from bottles in toddlers aged 11 to 13 months in a randomized controlled trial. We show in all four two-part models that the intervention promoted bottle-weaning and reduced daily milk intake from bottles in toddlers drinking from a bottle. We also show that there are no differences in model fit using either the logit link function or the probit link function for modeling the probability of bottle-weaning in all four models. Furthermore, prediction accuracy of the logit or probit link function is not sensitive to the distribution assumption on daily milk intake from bottles in toddlers not off bottles.

Keywords: two-part model, semi-continuous variable, truncated normal, gamma regression, skew normal, Pearson residual, receiver operating characteristic curve

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Authors: Pratibha, Jyoti Kori

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

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

Procedia PDF Downloads 185

Authors: Aditi Mittal, Nishit Gupta, Tina Dadu, Anil Handoo

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Introduction: Hematopoietic stem cell transplantation (HSCT) is a curative treatment done for hematologic malignancies and other clinical conditions. Its main objective is to reconstitute the hematopoietic system of the recipient by administering an infusion of donor hematopoietic stem cells. Transplant engraftment is the first sign of bone marrow recovery. The main objective of this study is to assess immature platelet fraction (IPF) and immature reticulocyte fraction (IRF) as early indicators of post-hematopoietic stem cell transplant engraftment. Methods: Patients of all age groups and both genders undergoing both autologous and allogeneic transplants were included in the study. All the CBC samples were run on Mindray CAL-8000 (BC-6800 plus; Shenzhen, China) analyser and assessed for IPF and IRF. Neutrophil engraftment was defined as the first of three consecutive days with an ANC >0.5 x 109/L and platelet engraftment with a count >20 x 109/L. The cut-off values for IRF were calculated as 13.5% with a CV of 5% and for IPF was 19% with a CV of 12%. Results: The study sample comprised 200 patients, of whom 116 had undergone autologous HSCT, and 84 had undergone allogeneic HSCT. We observed that IRF anticipated the neutrophil recovery by an average of 5 days prior to IPF. Though there was no significant variation in IPF and IRF for the prediction of platelet recovery, IRF was preceded by 1 or 2 days to IPF in 25% of cases. Conclusions: Both IPF and IRF can be used as reliable parameters as predictors for post-transplant engraftment; however, IRF seems to be more reliable than IPF as a simple, inexpensive, and widely available tool for predicting marrow recovery several days before engraftment.

Keywords: transplantation, stem cells, reticulocyte, engraftment

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Authors: K. H. Teng, A. Shaw, M. Ateeq, A. Al-Shamma'a, S. Wylie, S. N. Kazi, B. T. Chew

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Numerical and experimental of using novel electromagnetic wave technique to detect water hardness concentration has been presented in this paper. Simulation is powerful and efficient engineering methods which allow for a quick and accurate prediction of various engineering problems. The RF module is used in this research to predict and design electromagnetic wave propagation and resonance effect of a guided wave to detect water hardness concentration in term of frequency domain, eigenfrequency, and mode analysis. A cylindrical cavity resonator is simulated and designed in the electric field of fundamental mode (TM010). With the finite volume method, the three-dimensional governing equations were discretized. Boundary conditions for the simulation were the cavity materials like aluminum, two ports which include transmitting and receiving port, and assumption of vacuum inside the cavity. The design model was success to simulate a fundamental mode and extract S21 transmission signal within 2.1 – 2.8 GHz regions. The signal spectrum under effect of port selection technique and dielectric properties of different water concentration were studied. It is observed that the linear increment of magnitude in frequency domain when concentration increase. The numerical results were validated closely by the experimentally available data. Hence, conclusion for the available COMSOL simulation package is capable of providing acceptable data for microwave research.

Keywords: electromagnetic wave technique, frequency domain, signal spectrum, water hardness concentration

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Authors: Michaela Dušková, Kateřina Šimůnková, Martin Hill, Hana Hruškovičová, Hana Pospíšilová, Eva Králíková, Luboslav Stárka

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Smoking represents the most widespread substance dependence in the world. Several studies show the nicotine's ability to alter women hormonal homeostasis. Women smokers have higher testosterone and lower estradiol levels throughout life compared to non-smoker women. We monitored the effect of smoking discontinuation on steroid spectrum with 40 premenopausal and 60 postmenopausal women smokers. These women had been examined before they discontinued smoking and also after 6, 12, 24, and 48 weeks of abstinence. At each examination, blood was collected to determine steroid spectrum (measured by GC-MS), LH, FSH, and SHBG (measured by IRMA). Repeated measures ANOVA model was used for evaluation of the data. The study has been approved by the local Ethics Committee. Given the small number of premenopausal women who endured not to smoke, only the first 6 week period data could be analyzed. A slight increase in androgens after the smoking discontinuation occurred. In postmenopausal women, an increase in testosterone, dihydrotestosterone, dehydroepiandrosterone, and other androgens occurred, too. Nicotine replacement therapy, weight changes, and age does not play any role in the androgen level increase. The higher androgens levels correlated with failure in smoking cessation. Women smokers have higher androgen levels, which might play a role in smoking dependence development. Women successful in smoking cessation, compared to the non-successful ones, have lower androgen levels initially and also after smoking discontinuation. The question is what androgen levels women have before they start smoking.

Keywords: addiction, smoking, cessation, androgens

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Authors: Ali Abbas

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This paper presents a descriptive model of organizational misconduct based on observed patterns that occur before and after an ethical collapse. The patterns were classified by categorizing media articles in both "for-profit" and "not-for-profit" organizations. Based on the model parameters, the paper provides a descriptive model of various organizational deflection strategies under numerous scenarios, including situations where ethical complaints build-up, situations under which whistleblowers become more prevalent, situations where large scandals that relate to leadership occur, and strategies by which organizations deflect blame when pressure builds up or when media finds out. The model parameters start with the premise of a tolerance to double standards in unethical acts when conducted by leadership or by members of corporate governance. Following this premise, the model explains how organizations engage in discursive strategies to cover up the potential conflicts that arise, including secret agreements and weakening stakeholders who may oppose the organizational acts. Deflection strategies include "preemptive" and "post-complaint" secret agreements, absence of (or vague) documented procedures, engaging in blame and scapegoating, remaining silent on complaints until the media finds out, as well as being slow (if at all) to acknowledge misconduct and fast to cover it up. The results of this paper may be used to guide organizational leaders into the implications of such shortsighted strategies toward unethical acts, even if they are deemed legal. Validation of the model assumptions through numerous media articles is provided.

Keywords: ethical decision making, prediction, scandals, organizational strategies

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Authors: Maria Amodeo, Pasquale Arpaia, Marco Buzio, Vincenzo Di Capua, Francesco Donnarumma

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Different deep neural network architectures have been compared and tested to predict magnetic hysteresis in the context of pulsed electromagnets for experimental physics applications. Modelling quasi-static or dynamic major and especially minor hysteresis loops is one of the most challenging topics for computational magnetism. Recent attempts at mathematical prediction in this context using Preisach models could not attain better than percent-level accuracy. Hence, this work explores neural network approaches and shows that the architecture that best fits the measured magnetic field behaviour, including the effects of hysteresis and eddy currents, is the nonlinear autoregressive exogenous neural network (NARX) model. This architecture aims to achieve a relative RMSE of the order of a few 100 ppm for complex magnetic field cycling, including arbitrary sequences of pseudo-random high field and low field cycles. The NARX-based architecture is compared with the state-of-the-art, showing better performance than the classical operator-based and differential models, and is tested on a reference quadrupole magnetic lens used for CERN particle beams, chosen as a case study. The training and test datasets are a representative example of real-world magnet operation; this makes the good result obtained very promising for future applications in this context.

Keywords: deep neural network, magnetic modelling, measurement and empirical software engineering, NARX

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: Praveen Kumar, Nitin Kumar, Hemant Kumar

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The modernization of computer technology and commercial computational fluid dynamic (CFD) simulation has given better detailed results as compared to experimental investigation techniques. CFD techniques are widely used in different field due to its flexibility and performance. Evaluation of pipeline erosion is complex phenomenon to solve by numerical arithmetic technique, whereas CFD simulation is an easy tool to resolve that type of problem. Erosion wear behaviour due to solid–liquid mixture in the slurry pipeline has been investigated using commercial CFD code in FLUENT. Multi-phase Euler-Lagrange model was adopted to predict the solid particle erosion wear in 22.5° pipe bend for the flow of bottom ash-water suspension. The present study addresses erosion prediction in three dimensional 22.5° pipe bend for two-phase (solid and liquid) flow using finite volume method with standard k-ε turbulence, discrete phase model and evaluation of erosion wear rate with varying velocity 2-4 m/s. The result shows that velocity of solid-liquid mixture found to be highly dominating parameter as compared to solid concentration, density, and particle size. At low velocity, settling takes place in the pipe bend due to low inertia and gravitational effect on solid particulate which leads to high erosion at bottom side of pipeline.

Keywords: computational fluid dynamics (CFD), erosion, slurry transportation, k-ε Model

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Authors: Ekemini M. Okon, Reuben C. Okocha, Babatunde T. Adesina, Judith O. Ehigie, Babatunde M. Falana, Boluwape T. Okikiola

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Antimicrobial resistance (AMR) has evolved to become a significant threat to global public health and food safety. The development of AMR in animals has been associated with antimicrobial overuse. In recent years, the number of antimicrobials used in food animals such as fish and poultry has escalated. It, therefore, becomes imperative to understand the patterns of AMR in fish and poultry and map out future directions for better surveillance efforts. This study used the Preferred Reporting Items for Systematic reviews and Meta-Analyses(PRISMA) to assess the trend, patterns, and spatial distribution for AMR research in Egypt, Nigeria, and South Africa. A literature search was conducted through the Scopus and Web of Science databases in which published studies on AMR between 1989 and 2021 were assessed. A total of 172 articles were relevant for this study. The result showed progressive attention on AMR studies in fish and poultry from 2018 to 2021 across the selected countries. The period between 2018 (23 studies) and 2021 (25 studies) showed a significant increase in AMR publications with a peak in 2019 (28 studies). Egypt was the leading exponent of AMR research (43%, n=74) followed by Nigeria (40%, n=69), then South Africa (17%, n=29). AMR studies in fish received relatively little attention across countries. The majority of the AMR studies were on poultry in Egypt (82%, n=61), Nigeria (87%, n=60), and South Africa (83%, n=24). Further, most of the studies were on Escherichia and Salmonella species. Antimicrobials frequently researched were ampicillin, erythromycin, tetracycline, trimethoprim, chloramphenicol, and sulfamethoxazole groups. Multiple drug resistance was prevalent, as demonstrated by antimicrobial resistance patterns. In poultry, Escherichia coli isolates were resistant to cefotaxime, streptomycin, chloramphenicol, enrofloxacin, gentamycin, ciprofloxacin, oxytetracycline, kanamycin, nalidixic acid, tetracycline, trimethoprim/sulphamethoxazole, erythromycin, and ampicillin. Salmonella enterica serovars were resistant to tetracycline, trimethoprim/sulphamethoxazole, cefotaxime, and ampicillin. Staphylococcusaureus showed high-level resistance to streptomycin, kanamycin, erythromycin, cefoxitin, trimethoprim, vancomycin, ampicillin, and tetracycline. Campylobacter isolates were resistant to ceftriaxone, erythromycin, ciprofloxacin, tetracycline, and nalidixic acid at varying degrees. In fish, Enterococcus isolates showed resistance to penicillin, ampicillin, chloramphenicol, vancomycin, and tetracycline but sensitive to ciprofloxacin, erythromycin, and rifampicin. Isolated strains of Vibrio species showed sensitivity to florfenicol and ciprofloxacin, butresistance to trimethoprim/sulphamethoxazole and erythromycin. Isolates of Aeromonas and Pseudomonas species exhibited resistance to ampicillin and amoxicillin. Specifically, Aeromonashydrophila isolates showed sensitivity to cephradine, doxycycline, erythromycin, and florfenicol. However, resistance was also exhibited against augmentinandtetracycline. The findings constitute public and environmental health threats and suggest the need to promote and advance AMR research in other countries, particularly those on the global hotspot for antimicrobial use.

Keywords: antibiotics, antimicrobial resistance, bacteria, environment, public health

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Authors: Camila Amin-Puello, Lina Vasco-Diaz, Juan Ramirez-Arias, Claudia Munoz, Carlos Gonzalez-Calderon

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Operational flexibility is a fundamental aspect in the field of airlines because although demand is constantly changing, it is the duty of companies to provide a service to users that satisfies their needs in an efficient manner without sacrificing factors such as comfort, safety and other perception variables. The objective of this research is to understand the factors that describe and explain operational flexibility by implementing advanced analytical methods such as exploratory factor analysis and structural equation modeling, examining multiple levels of operational flexibility and understanding how these variable influences users' decision-making when choosing an airline and in turn how it affects the airlines themselves. The use of a hybrid model and latent variables improves the efficiency and accuracy of airline performance prediction in the unpredictable Colombian market. This pioneering study delves into traveler motivations and their impact on domestic flight demand, offering valuable insights to optimize resources and improve the overall traveler experience. Applying the methods, it was identified that low-cost airlines are not useful for flexibility, while users, especially women, found airlines with greater flexibility in terms of ticket costs and flight schedules to be more useful. All of this allows airlines to anticipate and adapt to their customers' needs efficiently: to plan flight capacity appropriately, adjust pricing strategies and improve the overall passenger experience.

Keywords: hybrid choice model, airline, business travelers, domestic flights

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Authors: Rahul Paliwal, Gulshan Maheshwari, Anant S. Jhaveri, Channamallikarjun S. Mathpati

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Large pumping facility is the necessary requirement of the cooling water systems for power plants, process and manufacturing facilities, flood control and water or waste water treatment plant. With a large capacity of few hundred to 50,000 m3/hr, cares must be taken to ensure the uniform flow to the pump to limit vibration, flow induced cavitation and performance problems due to formation of air entrained vortex and swirl flow. Successful prediction of these phenomena requires numerical method and turbulence model to characterize the dynamics of these flows. In the past years, single phase shear stress transport (SST) Reynolds averaged Navier Stokes Models (like k-ε, k-ω and RSM) were used to predict the behavior of flow. Literature study showed that two phase model will be more accurate over single phase model. In this paper, a 3D geometries simulated using detached eddy simulation (LES) is used to predict the behavior of the fluid and the results are compared with experimental results. Effect of different grid structure and boundary condition is also studied. It is observed that two phase flow model can more accurately predict the mean flow and turbulence statistics compared to the steady SST model. These validate model will be used for further analysis of vortex structure in lab scale model to generate their frequency-plot and intensity at different location in the set-up. This study will help in minimizing the ill effect of vortex on pump performance.

Keywords: grid structure, pump intake, simulation, vibration, vortex

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Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

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Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

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Authors: Janet Ige, Paul Pilkington, Selena Gray, Jane Powell

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Older adults from socially disadvantaged groups and Black and Minority Ethnic (BME) groups experience a higher burden of physical inactivity. Physical inactivity among BME groups is associated with the disproportionately higher level of health inequalities. People from minority ethnic groups encounter more barriers to physical activity. However, this is not often reported. There is very limited review-level evidence on the barriers and facilitators of physical activity among older adults from BME groups in the UK. This study aims to answer the following research question: what are the barriers and facilitators of physical activity participation among adults and older adults from BME background in the UK? To address this, we conducted a review of qualitative studies investigating the barriers and opportunities for physical activity among of BME adults and older adults in the UK. Method: This study is nested in an interpretive paradigm of meta-ethnography. A structured search for published literature was conducted on 6 electronic databases (MEDLINE, PsychINFO, Cumulative Index to Nursing & Allied Health Literature, Applied Social Sciences Index and Abstracts, Cochrane Database of Systematic Reviews, Allied and Complementary Medicine) from January 2007 to July 2017. Hand searching of the reference list of publications was performed in addition to a search conducted on Google Scholar to identify grey literature. Studies were eligible provided they employed any qualitative method and included participants identified as being BME, aged 50 and above, living in any community within the UK. In total, 1036 studies were identified from the structured search for literature, 718 studies were screened by titles after duplicates were removed. On applying the inclusion and exclusion criteria, a final selection of 10 studies was considered eligible for synthesis. Quality assessment was performed using the Critical Appraisal Skills Programme tool. Logic maps were used to show the relationship between factors that impact on physical activity participation among adults and older adults Result: Six key themes emerged from the data: awareness of the links between physical activity and health, interaction, and engagement with health professionals, cultural expectations and social responsibilities, appropriate environment, religious fatalism and practical challenges. Findings also showed that the barriers and facilitators of physical activity exist at the individual, community, and socio-economic, cultural and environmental level. There was a substantial gap in research among Black African groups. Findings from the review also informed the design of an ongoing survey investigating the experience and attitude of adults from Somali backgrounds towards physical activity in the UK. Conclusion: Identifying the barriers and facilitators of physical activity among BME groups is a crucial step in addressing the widening inequality gap. Findings from this study highlight the importance of engaging local BME residents in the design of exercise facilities within the community. This will ensure that cultural and social concerns are recognized and properly addressed.

Keywords: BME, UK, meta-ethnographic, adults

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Authors: Paschal A. Ochang, Emmanuel C. Oji

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The Duffing’s Equation is a second order system that is very important because they are fundamental to the behaviour of higher order systems and they have applications in almost all fields of science and engineering. In the biological area, it is useful in plant stem dependence and natural frequency and model of the Brain Crash Analysis (BCA). In Engineering, it is useful in the study of Damping indoor construction and Traffic lights and to the meteorologist it is used in the prediction of weather conditions. However, most Problems in real life that occur are non-linear in nature and may not have analytical solutions except approximations or simulations, so trying to find an exact explicit solution may in general be complicated and sometimes impossible. Therefore we aim to find out if it is possible to obtain one analytical fixed point to the non-linear ordinary equation using fixed point analytical method. We started by exposing the scope of the Duffing’s equation and other related works on it. With a major focus on the fixed point and fixed point iterative scheme, we tried different iterative schemes on the Duffing’s Equation. We were able to identify that one can only see the fixed points to a Damped Duffing’s Equation and not to the Undamped Duffing’s Equation. This is because the cubic nonlinearity term is the determining factor to the Duffing’s Equation. We finally came to the results where we identified the stability of an equation that is damped, forced and second order in nature. Generally, in this research, we approximate the solution of Duffing’s Equation by converting it to a system of First and Second Order Ordinary Differential Equation and using Fixed Point Iterative approach. This approach shows that for different versions of Duffing’s Equations (damped), we find fixed points, therefore the order of computations and running time of applied software in all fields using the Duffing’s equation will be reduced.

Keywords: damping, Duffing's equation, fixed point analysis, second order differential, stability analysis

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