Search results for: heart rate variability (HRV)

Authors: Shih-Kuei Lin

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The characterization of the arbitrage-free dynamics of interest rates is developed in this study under the presence of Markov jump risks, when the term structure of the interest rates is modeled through simple forward rates. We consider Markov jump risks by allowing randomness in jump sizes, independence between jump sizes and jump times. The Markov jump diffusion model is used to capture empirical phenomena and to accurately describe interest jump risks in a financial market. We derive the arbitrage-free model of simple forward rates under the spot measure. Moreover, the analytical pricing formulas for a cap and a floor are derived under the forward measure when the jump size follows a lognormal distribution. In our empirical analysis, we find that the LIBOR market model with Markov jump risk better accounts for changes from/to different states and different rates.

Keywords: arbitrage-free, cap and floor, Markov jump diffusion model, simple forward rate model, volatility smile, EM algorithm

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Authors: Bounar Nedjemeddine

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Materials with the pyrochlore lattice structure have attracted much recent attention due to their wide applications in ceramic thermal barrier coatings, high-permittivity dielectrics, and potential solid electrolytes in solid-oxide fuel cells. The work described in this paper is devoted to the synthesis and characterization of a pyrochlore structure based on lanthanum (La₂O₃) and tin (SnO₂) oxides of general formula La₂Sn₂O₇, substituted by Sr at the site La. Their structures were determined from X-ray powder diffraction using CELFER analysis. All the compositions present the space group Fd-3m. The substitution of La by Sr in the La₂Sn₂O₇ compound causes a variation of the cell parameters. The difference in charge between La³⁺ and Sr²⁺ and the difference in size cause the cell parameters to decrease from a=10.7165 A° to a=10.6848 A° for the substitution rates (x = 0.05, 0.1, 0.15 ...), which leads to a decrease in the volume of the mesh. For a substitution rate x = 0.25, there is an increase in the cell parameters (a=10.7035A°), which can be explained by a competitiveness of the size effect and the presence of a gap in the structure which go in the opposite direction.

Keywords: solid-oxide fuel cells, structure, pyrochlore, X-ray diffraction

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Authors: L. Bidyalakshmi, R. Ananthan, T. Longvah

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Antioxidants are substances that can prevent or delay oxidative damage of lipids, proteins and nucleic acids by reactive oxygen species. These help in lowering incidence of degenerative diseases such as cancer, arthritis, atherosclerosis, heart disease, inflammation, brain dysfunction and acceleration of the ageing process. The north eastern part of India falls among the global hotspots of biodiversity. Over the years, the local communities in the region have developed ingenious uses of many wild plants within their environment as food sources. Many of these less familiar foods form an integral part of the diet of these communities, and some are traditionally valued for its therapeutic effects. So the study was carried to estimate the antioxidant activity of some of these indigenous foods. Twenty-eight indigenous plant foods were studied for their antioxidant activity. Antioxidant activities were determined by using DPPH (2, 2-diphenyl-1-picrylhydrazyl) assay, FRAP (Ferric Reducing Antioxidant Power) assay and SOSA (Super Oxide Scavenging Assay). Out of the twenty-eight plant foods, there were thirteen leafy vegetables, four fruits, five roots and tubers, four spices and two mushrooms. Water extract and methanol extract of the samples were used for the analysis. The leafy vegetable samples exhibited antioxidant capacity with IC50 ranging from 8-1414 mg/ml for lipid extract and 34-37878 mg/ml for aqueous extract in DPPH assay. Total FRAP value ranging from 58-1005 mmol FeSO4 Eq/100g of the sample, which is comparatively higher than the antioxidant capacity of some commonly consumed leafy vegetables. In SOSA, water extract of leafy vegetables show a range of 0.05-193.68 µmol ascorbic acid equivalent/g of the samples. While the methanol extract of the samples show 0.20-21.94 µmol Trolox equivalent/g of the samples. Polygonum barbatum, Wendlandia glabrata and Polygonum posumbu have higher antioxidant activity among the leafy vegetables analysed. Among the fruits, Rhus hookerii showed the highest antioxidant activities in both FRAP and SOSA methods while Spondias magnifera exhibited higher antioxidant activity in DPPH method. Alocasia cucullata exhibited higher antioxidant activity in DPPH and FRAP assays while Alpinia galanga showed higher antioxidant activity in SOSA assay when compared to the other samples of roots and tubers. Elsholtzia communis showed high antioxidant activity in all the three parameters among the spices. For the mushrooms, Pleurotus ostreatus exhibited higher antioxidant activity than Auricularia delicate in DPPH and SOSA. The samples analysed exhibited antioxidant activity at varying levels and some exhibited higher antioxidant activity than the commonly consumed foods. So consumption of these less familiar foods may play a role in preventing human disease in which free radicals are involved. Further studies on these food samples on phytonutrients and its contribution to the antioxidant activities are required.

Keywords: antioxidant activity, DPPH, FRAP, SOSA

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Authors: Mikko Salminen, Niklas Ravaja

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Previous studies have shown that emotional intelligence (EI) has an important role in leadership and social interaction. On the other hand, physiological synchronization between two interacting participants has been related to, for example, intensity of the interaction, and interestingly also to empathy. It is suggested that the amount of covariation in physiological signals between the two interacting persons would also be related to how the discussion is perceived subjectively. To study the interrelations between physiological synchronization, emotional intelligence, and subjective perception of the interaction, performance review discussions between real manager – subordinate dyads were studied using psychophysiological measurements and self-reports. The participants consisted of 40 managers, of which 24 were female, and 78 of their subordinates, of which 45 were female. The participants worked in various fields, for example banking, education, and engineering. The managers had a normal performance review discussion with two subordinates, except two managers who, due to scheduling issues, had discussion with only one subordinate. The managers were on average 44.5 years old, and the subordinates on average 45.5 years old. Written consent, in accordance with the Declaration of Helsinki, was obtained from all the participants. After the discussion, the participants filled a questionnaire assessing their emotions during the discussion. This included a self-assessment manikin (SAM) scale for the emotional valence during the discussion, with a 9-point graphical scale representing a manikin whose facial expressions ranged from smiling and happy to frowning and unhappy. In addition, the managers filled EI360, a 37-item self-report trait emotional intelligence questionnaire. The psychophysiological activity of the participants was recorded using two Varioport-B portable recording devices. Cardiac activity (ECG, electrocardiogram) was measured with two electrodes placed on the torso. Inter-beat interval (IBI, time between two successive heart beats) was calculated from the ECG signals. The facial muscle activation (EMG, electromyography) was recorded on three sites of the left side of the face: zygomaticus major (cheek muscle), orbicularis oculi (periocular muscle), and corrugator supercilii (frowning muscle). The facial-EMG signals were rectified and smoothed, and cross-coherences were calculated between members of each dyad, for all the three EMG signals, for the baseline and discussion periods. The values were natural-log transformed to normalize the distributions. Higher cross-coherence during the discussion between the manager’s and the subordinate’s zygomatic muscles was related to more positive valence self-reported emotions, F(1; 66,137) = 7,051; p=0,01. Thus, synchronized cheek muscle activation, either due to synchronous smiling or talking, was related to more positive perception of the discussion. In addition, higher IBI synchronization between the manager and the subordinate during the discussion was related to the manager’s higher self-reported emotional intelligence, F(1; 27,981)=4,58; p=0,041. That is, the EI was related to synchronous cardiac activity and possibly to similar physiological arousal levels. The results imply that the psychophysiological synchronization could be a potentially useful index in the study of social interaction and a valuable tool in the coaching of leadership skills in organizational contexts.

Keywords: emotional intelligence, leadership, psychophysiology, social interaction, synchronization

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Authors: Ravinesh C. Deo

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This article reviews the role of nozzle-exit conditions on the flow field of a plane jet. The jet issuing from a sharp-edged orifice plate at a Reynolds number (Re=18000) with nozzle aspect ratio (AR=72) exhibits the greatest shear-layer instabilities, highest entrainment and jet-spreading rates compared to the radially contoured nozzle. The growth rate of the shear-layer is the highest for the orifice-jet although this property could be amplified for larger Re or AR. A local peak in turbulent energy is found at x=10h. The peak appears to be elevated for an orifice-jet with lower Re or AR. The far-field energy sustained by the orifice-jet exceeds the contoured case although a higher Re and AR may enhance this value. The spectra displays the largest eddies generated by the contoured nozzle. However, the frequency of coherent eddies is higher for the orifice-jet, with a larger magnitude achievable for lower Re and AR.

Keywords: plane jet, Reynolds number, nozzle-exit conditions, nozzle geometry, aspect ratio

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Authors: X. Simon, D. Copena, M. Montero

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The last decades have witnessed a significant increase in renewable energy, especially wind energy, to achieve sustainable development. Specialized literature in this field has carried out interesting case studies to extensively analyze both the environmental benefits of this energy and its social acceptance. However, to the best of our knowledge, work to date makes no analysis of the role of private owners of lands with wind potential within a broader territory of strong wind implantation, nor does it estimate their economic incomes relating them to social acceptance. This work fills this gap by focusing on Galicia, territory housing over 4,000 wind turbines and almost 3,400 MW of power. The main difficulty in getting this financial information is that it is classified, not public. We develop methodological techniques (semi- structured interviews and work groups), inserted within the Participatory Research, to overcome this important obstacle. In this manner, the work directly compiles qualitative and quantitative information on the processes as well as the economic results derived from implementing wind energy in Galicia. During the field work, we held 106 semi-structured interviews and 32 workshops with owners of lands occupied by wind farms. The compiled information made it possible to create the socioeconomic database on wind energy in Galicia (SDWEG). This database collects a diversity of quantitative and qualitative information and contains economic information on the income received by the owners of lands occupied by wind farms. In the Galician case, regulatory framework prevented local participation under the community wind farm formula. The possibility of local participation in the new energy model narrowed down to companies wanting to install a wind farm and demanding land occupation. The economic mechanism of local participation begins here, thus explaining the level of acceptance of wind farms. Land owners can receive significant income given that these payments constitute an important source of economic resources, favor local economic activity, allow rural areas to develop productive dynamism projects and improve the standard of living of rural inhabitants. This work estimates that land owners in Galicia perceive about 10 million euros per year in total wind revenues. This represents between 1% and 2% of total wind farm invoicing. On the other hand, relative revenues (Euros per MW), far from the amounts reached in other spaces, show enormous payment variability. This signals the absence of a regulated market, the predominance of partial agreements, and the existence of asymmetric positions between owners and developers. Sustainable development requires the replacement of conventional technologies by low environmental impact technologies, especially those that emit less CO₂. However, this new paradigm also requires rural owners to participate in the income derived from the structural transformation processes linked to sustainable development. This paper demonstrates that regulatory framework may contribute to increasing sustainable technologies with high social acceptance without relevant local economic participation.

Keywords: regulatory framework, social acceptance, sustainable development, wind energy, wind income for landowners

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Authors: Nisrine Benzbiria, Mohammed Azzi, Mustapha Zertoubi

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2XXX series of aluminum alloys are widely employed in several applications, such as beverages, automotive, and aerospace industries. However, they are particularly prone to localized corrosion, such as pitting, often induced by a difference in corrosion potential measured for intermetallic phases and pure metal. The galvanic cells comprising Al–Cu– Mn–Fe intermetallic phases control cathodically the dissolution rate as oxygen reduction reaction kinetics are privileged on Al–Cu–Mn–Fe particles. Hence, understanding the properties of cathode sites and the processes involved must be carried out. Our interest is to outline the cathodic behavior of AA2024-T3 in sodium sulfate solution using electrochemical techniques. Oxygen reduction reaction (ORR) was investigated in the mixed charge transfer and mass transport regime using the Koutecky-Levich approach. An environmentally benign inhibitor was considered to slow the ORR on the Cu-rich cathodic phases. The surface morphology of the electrodes was investigated with SEM/EDS and AFM. The obtained results were discussed accordingly.

Keywords: AA2024-T3, neutral medium, ORR kinetics, Koutecky-Levich, DFT

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Authors: Preshanthan Moodley, E. B. Gueguim Kana

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This study examines the kinetics of S. cerevisiae BY4743 growth and bioethanol production from sugarcane leaf waste (SLW), utilizing two different optimized pretreatment regimes; under two fermentation modes: steam salt-alkali filtered enzymatic hydrolysate (SSA-F), steam salt-alkali unfiltered (SSA-U), microwave salt-alkali filtered (MSA-F) and microwave salt-alkali unfiltered (MSA-U). The kinetic coefficients were determined by fitting the Monod, modified Gompertz, and logistic models to the experimental data with high coefficients of determination R² > 0.97. A maximum specific growth rate (µₘₐₓ) of 0.153 h⁻¹ was obtained under SSA-F and SSA-U whereas, 0.150 h⁻¹ was observed with MSA-F and MSA-U. SSA-U gave a potential maximum bioethanol concentration (Pₘ) of 31.06 g/L compared to 30.49, 23.26 and 21.79g/L for SSA-F, MSA-F and MSA-U respectively. An insignificant difference was observed in the μmax and Pm for the filtered and unfiltered enzymatic hydrolysate for both SSA and MSA pretreatments, thus potentially reducing a unit operation. These findings provide significant insights for process scale up.

Keywords: lignocellulosic bioethanol, microwave pretreatment, sugarcane leaves, kinetics

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: Katerina Nerantzaki, Panayiota Metallidou, Anastasia Efklides

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The aim of the study was to investigate: (a) changes in the intensity of various epistemic emotions during cognitive processing in a decision-making task and (b) their associations with metacognitive feelings of difficulty and confidence. One hundred and fifty-two undergraduate university students were asked individually to read in the e-prime environment decision-making scenarios about moral dilemmas concerning self-driving cars, which differed in the level of conflict they produced, and then to make a choice between two options. Further, the participants were asked to rate on a four-point scale four epistemic emotions (surprise, curiosity, confusion, and wonder) and two metacognitive feelings (feeling of difficulty and feeling of confidence) after making their choice in each scenario. Changes in cognitive processing due to the level of conflict affected differently the intensity of the specific epistemic emotions. Further, there were interrelations of epistemic emotions with metacognitive feelings.

Keywords: confusion, curiosity, epistemic emotions, metacognitive experiences, surprise

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Authors: S. Bouharati, F. Allag, M. Belmahdi, M. Bounechada

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In terms of ecology forecast effects of desertification, the purpose of this study is to develop a predictive model of growth and adaptation of species in arid environment and bioclimatic conditions. The impact of climate change and the desertification phenomena is the result of combined effects in magnitude and frequency of these phenomena. Like the data involved in the phytopathogenic process and bacteria growth in arid soil occur in an uncertain environment because of their complexity, it becomes necessary to have a suitable methodology for the analysis of these variables. The basic principles of fuzzy logic those are perfectly suited to this process. As input variables, we consider the physical parameters, soil type, bacteria nature, and plant species concerned. The result output variable is the adaptability of the species expressed by the growth rate or extinction. As a conclusion, we prevent the possible strategies for adaptation, with or without shifting areas of plantation and nature adequate vegetation.

Keywords: climate changes, dry soil, phytopathogenicity, predictive model, fuzzy logic

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Authors: Abdulqader Almasabe, Stephanie Ludi, Mohammed Alenazi

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Governments around the world have been increasingly introducing e-government services in order to make processes more efficient and accessible for their citizens. The government of Saudi Arabia has adopted E-Government for the effective delivery of services. However, the adoption rate of these services remains low in many countries. This paper aims to explore the determinants of citizens' intention to adopt and use e-government services, focusing on a model of factors influencing the adoption and utilization of e-government services (MFIAUEGS) that has been specially developed for this purpose. By analyzing the factors that influence citizens' decisions to use e-government services we hope to provide insights that help to increase adoption rates and improve the overall effectiveness of these services. In this paper, 562 valid responses were collected and analyzed to shed light on the issue. The results of the research showed that each of the proposed factors in the MFIAUEGS model played a significant role in influencing citizens' intentions to adopt and use e-government services.

Keywords: e-government, model acceptance, influencing factors, TAM

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Authors: Meitham Amereh, Mohsen Akbari, Ben Nadler

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Cancer has been recognized as one of the most challenging problems in biology and medicine. Aggressive tumors are a lethal type of cancers characterized by high genomic instability, rapid progression, invasiveness, and therapeutic resistance. Their behavior involves complicated molecular biology and consequential dynamics. Although tremendous effort has been devoted to developing therapeutic approaches, there is still a huge need for new insights into the dark aspects of tumors. As one of the key requirements in better understanding the complex behavior of tumors, mathematical modeling and continuum physics, in particular, play a pivotal role. Mathematical modeling can provide a quantitative prediction on biological processes and help interpret complicated physiological interactions in tumors microenvironment. The pathophysiology of aggressive tumors is strongly affected by the extracellular cues such as stresses produced by mechanical forces between the tumor and the host tissue. During the tumor progression, the growing mass displaces the surrounding extracellular matrix (ECM), and due to the level of tissue stiffness, stress accumulates inside the tumor. The produced stress can influence the tumor by breaking adherent junctions. During this process, the tumor stops the rapid proliferation and begins to remodel its shape to preserve the homeostatic equilibrium state. To reach this, the tumor, in turn, upregulates epithelial to mesenchymal transit-inducing transcription factors (EMT-TFs). These EMT-TFs are involved in various signaling cascades, which are often associated with tumor invasiveness and malignancy. In this work, we modeled the tumor as a growing hyperplastic mass and investigated the effects of mechanical stress from surrounding ECM on tumor invasion. The invasion is modeled as volume-preserving inelastic evolution. In this framework, principal balance laws are considered for tumor mass, linear momentum, and diffusion of nutrients. Also, mechanical interactions between the tumor and ECM is modeled using Ciarlet constitutive strain energy function, and dissipation inequality is utilized to model the volumetric growth rate. System parameters, such as rate of nutrient uptake and cell proliferation, are obtained experimentally. To validate the model, human Glioblastoma multiforme (hGBM) tumor spheroids were incorporated inside Matrigel/Alginate composite hydrogel and was injected into a microfluidic chip to mimic the tumor’s natural microenvironment. The invasion structure was analyzed by imaging the spheroid over time. Also, the expression of transcriptional factors involved in invasion was measured by immune-staining the tumor. The volumetric growth, stress distribution, and inelastic evolution of tumors were predicted by the model. Results showed that the level of invasion is in direct correlation with the level of predicted stress within the tumor. Moreover, the invasion length measured by fluorescent imaging was shown to be related to the inelastic evolution of tumors obtained by the model.

Keywords: cancer, invasion, mathematical modeling, microfluidic chip, tumor spheroids

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Authors: I. Gokasar, G. Bakioglu

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With the unprecedented rates of technological improvements, people start to solve their problems with the help of technological tools. According to application stores and websites in which people evaluate and comment on the traffic apps, there are more than 100 traffic applications which have different features with respect to their purpose of usage ranging from the features of traffic apps for public transit modes to the features of traffic apps for private cars. This study focuses on the top 30 traffic applications which were chosen with respect to their download counts. All data about the traffic applications were obtained from related websites. The purpose of this study is to analyze traffic applications in terms of their categorical attributes with the help of developing a regression model. The analysis results suggest that negative interpretations (e.g., being deficient) does not lead to lower star ratings of the applications. However, those negative interpretations result in a smaller increase in star rate. In addition, women use higher star rates than men for the evaluation of traffic applications.

Keywords: traffic app, real–time information, traffic congestion, regression analysis, dummy variables

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Authors: Hasan Kaya

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Effect of lead content on the microstructure, mechanical (microhardness, ultimate tensile strength) and electrical resistivity properties of Al–Si eutectic alloys has been investigated. Al–12.6 Si–xSn (x=1, 2, 4, 6 and 8 wt. %) were prepared using metals of 99.99% high purity in the vacuum atmosphere. These alloys were directionally solidified under constant temperature gradient (5.50 K/mm) and growth rate (8.25 μm/s) by using a Bridgman–type directional solidification furnace. Eutectic spacing, microhardness, ultimate tensile strength and electrical resistivity were expressed as functions of the composition by using a linear regression analysis. The dependency of the eutectic spacing, microhardness, tensile strength and electrical resistivity on the composition (Sn content) were determined. According to experimental results, the microhardness, ultimate tensile strength and electrical resistivity of the solidified samples increase with increasing the Sn content, but decrease eutectic spacing. Variation of electrical resistivity with the temperature in the range of 300-500 K for studied alloys was also measured by using a standard d.c. four-point probe technique.

Keywords: content elements, solidification, microhardness, strength

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Authors: Orkide Donma, Mustafa M. Donma

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Childhood obesity, which may lead to increased risk for heart diseases in children as well as adults, is one of the most important health problems throughout the world. Prevalences of morbid obesity and metabolic syndrome (MetS) are being increased during childhood age group. MetS is a cluster of metabolic and vascular abnormalities including hypercoagulability and an increased risk of cardiovascular diseases (CVDs). There are also some relations between some components of MetS and leukocytes. The aim of this study is to investigate complete blood cell count parameters that differ between morbidly obese boys and girls with MetS diagnosis. A total of 117 morbid obese children with MetS consulted to Department of Pediatrics in Faculty of Medicine Hospital at Namik Kemal University were included into the scope of the study. The study population was classified based upon their genders (60 girls and 57 boys). Their heights and weights were measured and body mass index (BMI) values were calculated. WHO BMI-for age and sex percentiles were used. The values above 99 percentile were defined as morbid obesity. Anthropometric measurements were performed. Waist-to-hip and head-to-neck ratios as well as homeostatic model assessment of insulin resistance (HOMA-IR) were calculated. Components of MetS (central obesity, glucose intolerance, high blood pressure, high triacylglycerol levels, low levels of high density lipoprotein cholesterol) were determined. Hematological variables were measured. Statistical analyses were performed using SPSS. The degree for statistical significance was p ≤ 0.05. There was no statistically significant difference between the ages (11.2±2.6 years vs 11.2±3.0 years) and BMIs (28.6±5.2 kg/m² vs 29.3±5.2 kg/m²) of boys and girls (p ≥ 0.05), respectively. Significantly increased waist-to-hip ratios were obtained for boys (0.94±0.08 vs 0.91±0.06; p=0.023). Significantly elevated values of hemoglobin (13.55±0.98 vs 13.06±0.82; p=0.004), mean corpuscular hemoglobin concentration (33.79±0.91 vs 33.21±1.14; p=0.003), eosinophils (0.300±0.253 vs 0.196±0.197; p=0.014), and platelet (347.1±81.7 vs 319.0±65.9; p=0.042) were detected for boys. There was no statistically significant difference between the groups in terms of neutrophil/lymphocyte ratios as well as HOMA-IR values (p ≥ 0.05). Statistically significant gender-based differences were found for hemoglobin as well as mean corpuscular hemoglobin concentration and hence, separate reference intervals for two genders should be considered for these parameters. Eosinophils may contribute to the development of thrombus in acute coronary syndrome. Eosinophils are also known to make an important contribution to mechanisms related to thrombosis pathogenesis in acute myocardial infarction. Increased platelet activity is observed in patients with MetS and these individuals are more susceptible to CVDs. In our study, elevated platelets described as dominant contributors to hypercoagulability and elevated eosinophil counts suggested to be related to the development of CVDs observed in boys may be the early indicators of the future cardiometabolic complications in this gender.

Keywords: children, complete blood count, gender, metabolic syndrome

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Authors: Suphat Rittirat, Sutha Klaocheed, Somporn Prasertsongskun, Kanchit Thammasiri

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Protocorms of Phalaenopsis cornu-cervi (Breda) Blume & Rchb. f. were successfully cryopreserved using a vitrification method. Two-month old protocorms at GI 4 stage were precultured in liquid MS medium supplemented with different concentrations of sucrose (0.3, 0.5, 0.7, 0.9 and 1.2 M) at 25±1°C for 2 days on an orbital shaker at 110 rpm. The protocorms were treated with loading solution (2 M glycerol plus 0.4 M sucrose) for 20 minutes at 25±1°C. Then, the protocorms were sufficiently dehydrated with vitrification solution (plant vitrification solution 2, PVS2) for various times (0, 30, 60, 90 and 120 minutes) at 25±1°C and stored in liquid nitrogen for 1 day. After rapid thawing in water bath at 40°C for 2 minutes, the explants were washed by MS liquid medium containing 0.5 ml of 1.2 M sucrose for 20 minutes. The results shown that the protocorms were precultured in liquid MS medium containing 0.5 M sucrose and dehydrated with vitrification solution for 60 minutes had the highest survival percentage of protocorm at 31±1.0 % as measured by Evan’s blue. No survival rate of protocorms was found without vitrification treatments.

Keywords: protocorms, cryopreservation, Phalaenopsis cornu-cervi, vitrification

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Authors: Rakesh Prajapati, Purvik Patel, Hardik Patel

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Productivity and quality are two important aspects that have become great concerns in today’s competitive global market. Every production/manufacturing unit mainly focuses on these areas in relation to the process, as well as the product developed. The electrical discharge machining (EDM) process, even now it is an experience process, wherein the selected parameters are still often far from the maximum, and at the same time selecting optimization parameters is costly and time consuming. Material Removal Rate (MRR) during the process has been considered as a productivity estimate with the aim to maximize it, with an intention of minimizing surface roughness taken as most important output parameter. These two opposites in nature requirements have been simultaneously satisfied by selecting an optimal process environment (optimal parameter setting). Objective function is obtained by Regression Analysis and Analysis of Variance. Then objective function is optimized using Genetic Algorithm technique. The model is shown to be effective; MRR and Surface Roughness improved using optimized machining parameters.

Keywords: MMR, TWR, OC, DOE, ANOVA, minitab

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Authors: Mohamed Hamada Abdelkader Fayed

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Background: To evaluate the diagnostic accuracy of (ADD-RS) with D-dimer as a screening test to exclude AAS. Methods: We conducted research for the studies examining the diagnostic accuracy of (ADD- RS)+ D-dimer to exclude the diagnosis of AAS, We searched MEDLINE, Embase, and Cochrane of Trials up to 31 December 2020. Results: We identified 3 studies using (ADD-RS) with D-dimer as a diagnostic tool for AAS, involving 3261 patients were AAS was diagnosed in 559(17.14%) patients. Overall results showed that the pooled sensitivities were 97.6 (95% CI 0.95.6, 99.6) at (ADD-RS)≤1(low risk group) with D-dimer and 97.4(95% CI 0.95.4,, 99.4) at (ADD-RS)>1(High risk group) with D-dimer., the failure rate was 0.48% at low risk group and 4.3% at high risk group respectively. Conclusions: (ADD-RS) with D-dimer was a useful screening test with high sensitivity to exclude Acute Aortic Syndrome.

Keywords: aortic dissection detection risk score, D-dimer, acute aortic syndrome, diagnostic accuracy

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Authors: Parisa Shirzadeh

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Drug delivery systems in which drugs are traditionally used, multi-stage and at specified intervals by patients, do not meet the needs of the world's up-to-date drug delivery. In today's world, we are dealing with a huge number of recombinant peptide and protean drugs and analogues of hormones in the body, most of which are made with genetic engineering techniques. Most of these drugs are used to treat critical diseases such as cancer. Due to the limitations of the traditional method, researchers sought to find ways to solve the problems of the traditional method to a large extent. Following these efforts, controlled drug release systems were introduced, which have many advantages. Using controlled release of the drug in the body, the concentration of the drug is kept at a certain level, and in a short time, it is done at a higher rate. Graphene is a natural material that is biodegradable, non-toxic, and natural compared to carbon nanotubes; its price is lower than carbon nanotubes and is cost-effective for industrialization. On the other hand, the presence of highly effective surfaces and wide surfaces of graphene plates makes it more effective to modify graphene than carbon nanotubes. Graphene oxide is often synthesized using concentrated oxidizers such as sulfuric acid, nitric acid, and potassium permanganate based on Hummer 1 method. In comparison with the initial graphene, the resulting graphene oxide is heavier and has carboxyl, hydroxyl, and epoxy groups. Therefore, graphene oxide is very hydrophilic and easily dissolves in water and creates a stable solution. On the other hand, because the hydroxyl, carboxyl, and epoxy groups created on the surface are highly reactive, they have the ability to work with other functional groups such as amines, esters, polymers, etc. Connect and bring new features to the surface of graphene. In fact, it can be concluded that the creation of hydroxyl groups, Carboxyl, and epoxy and in fact graphene oxidation is the first step and step in creating other functional groups on the surface of graphene. Chitosan is a natural polymer and does not cause toxicity in the body. Due to its chemical structure and having OH and NH groups, it is suitable for binding to graphene oxide and increasing its solubility in aqueous solutions. Graphene oxide (GO) has been modified by chitosan (CS) covalently, developed for control release of doxorubicin (DOX). In this study, GO is produced by the hummer method under acidic conditions. Then, it is chlorinated by oxalyl chloride to increase its reactivity against amine. After that, in the presence of chitosan, the amino reaction was performed to form amide transplantation, and the doxorubicin was connected to the carrier surface by π-π interaction in buffer phosphate. GO, GO-CS, and GO-CS-DOX characterized by FT-IR, RAMAN, TGA, and SEM. The ability to load and release is determined by UV-Visible spectroscopy. The loading result showed a high capacity of DOX absorption (99%) and pH dependence identified as a result of DOX release from GO-CS nanosheet at pH 5.3 and 7.4, which show a fast release rate in acidic conditions.

Keywords: graphene oxide, chitosan, nanosheet, controlled drug release, doxorubicin

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Authors: Nurul Na'imy Wan, Mohamad Sazali Said, Jaharah Ab. Ghani, Rusli Othman

Abstract:

This paper presents the surface roughness of the aluminium silicon alloy (AlSi) matrix composite which has been reinforced with aluminium nitride (AlN). Experiments were conducted at various cutting speeds, feed rates, and depths of cut, according to a standard orthogonal array L27 of Taguchi method using TiN coating tool of insert. The signal-to-noise (S/N) ratio and analysis of variance are applied to study the characteristic performance of cutting speeds, feed rates and depths of cut in measuring the surface roughness during the milling operation. The surface roughness was observed using Mitutoyo Formtracer CS-500 and analyzed using the Taguchi method. From the Taguchi analysis, it was found that cutting speed of 230 m/min, feed rate of 0.4 mm/tooth, depth of cut of 0.3 mm were the optimum machining parameters using TiN coating insert.

Keywords: AlSi/AlN metal matrix composite (MMC), surface roughness, Taguchi method, machining parameters

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Authors: T. Wejrzanowski, M. Grybczuk, E. Tymicki, K. J. Kurzydlowski

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In the present study, numerical simulations of heat and mass transfer in Physical Vapor Transport reactor during silicon carbide single crystal growth are addressed. Silicon carbide is a wide bandgap material with unique properties making it highly applicable for high power electronics applications. Because of high manufacturing costs improvements of SiC production process are required. In this study, numerical simulations were used as a tool of process optimization. Computer modeling allows for cost and time effective analysis of processes occurring during SiC single crystal growth and provides essential information needed for improvement of the process. Quantitative relationship between process conditions, such as temperature or pressure, and crystal growth rate and shape of crystallization front have been studied and verified using experimental data. Basing on modeling results, several process improvements were proposed and implemented.

Keywords: Finite Volume Method, semiconductors, Physica Vapor Transport, silicon carbide

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Authors: Kiumars Shahbazi, Salah Salimian, Abdolrahim Hashemi Dizaj

Abstract:

Locating is one of the key elements in success and survival of industrial centers and has great impact on cost reduction of establishment and launching of various economic activities. In this study, streets with unequal length model have been used that is the classic extension of Spoke model; however with unlimited number of streets with uneven lengths. The results showed that the spoke model is a special case of streets with unequal length model. According to the results of this study, if the strategy of enterprises and firms is to select both price and location, there would be no balance in the game. Furthermore, increased length of streets leads to increased profit of enterprises and with increased number of streets, the enterprises choose locations that are far from center (the maximum differentiation), and the enterprises' output will decrease. Moreover, the enterprise production rate will incline toward zero when the number of streets goes to infinity, and complete competition outcome will be achieved.

Keywords: locating, Nash equilibrium, streets with unequal length model, streets with unequal length model

Procedia PDF Downloads 187

Authors: Gyeong-Sung Kim, In-soo Ahn, Yong Cho

Abstract:

SBR (Sequencing Batch Reactor) process is usually applied to membrane water treatment plants to treat its concentrated wastewater. The role of SBR process is to remove COD (Chemical Oxygen Demand) and NH3 from wastewater before discharging it outside of the water treatment plant using microorganism. Microorganism’s nitrification capability is influenced by water temperature because the nitrification rate of the concentrated wastewater becomes ‘zero’ as water temperature approach 0℃. Heating system is necessary to operate SBR in winter season even though the operating cost increase sharply. The operating cost of SBR at ‘D’ RO water treatment plant in Korea was 51.8 times higher in winter (October to March) compare to summer (April to September) season in 2014. Otherwise the effluent water temperature maintained around 8℃ constantly in winter. This study focuses on application heat pump system to recover the thermal energy from the effluent water of ‘D’ RO plant so that the operating cost will be reduced.

Keywords: water treatment, water thermal energy, energy saving, RO, SBR

Procedia PDF Downloads 503

Authors: A. Natsir, M. Nadir, S. Syahrir, A. Mujnisa, N. Purnomo, A. R. Egan, B. J. Leury

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Rumen degradation characteristic of feedstuff is one of the prominent factors affecting microbial population in rumen of animal. High rumen degradation rate of faba bean protein may lead to inconstant rumen conditions that could have a prominent impact on rumen microbial diversity. Amplified Ribosomal DNA Restriction Analysis (ARDRA) is utilized to monitor diversity of rumen microbes on sheep fed low quality forage supplemented by faba beans. Four mature merino sheep with existing rumen cannula were used in this study according to 4 x 4 Latin square design. The results of study indicated that there were 37 different ARDRA types identified out of 136 clones examined. Among those clones, five main clone types existed across the treatments with different percentages. In conclusion, the ARDRA method is potential to be used as a routine tool to assess the temporary changes in the rumen community as a result of different feeding strategies.

Keywords: ARDRA method, cattle, genomic diversity, rumen microbes

Procedia PDF Downloads 341

Authors: Theophilus Adjirackor, Frederic Sam, Irene Opoku-Ntim, David Okoh Kpeglo, Prince K. Gyekye, Frank K. Quashie, Kofi Ofori

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Indoor radon concentrations were collected monthly over a period of one year in 10 different levels in an underground goldmine, and the data was analyzed using a four-moving average time series to determine the relationship between the depths of the underground mine and the indoor radon concentration. The detectors were installed in batches within four quarters. The measurements were carried out using LR115 solid-state nuclear track detectors. Statistical models are applied in the prediction and analysis of the radon concentration at various depths. The time series model predicted a positive relationship between the depth of the underground mine and the indoor radon concentration. Thus, elevated radon concentrations are expected at deeper levels of the underground mine, but the relationship was insignificant at the 5% level of significance with a negative adjusted R2 (R2 = – 0.021) due to an appropriate engineering and adequate ventilation rate in the underground mine.

Keywords: LR115, radon concentration, rime series, underground goldmine

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Authors: Esther Lorrayne M. Pereira, Adriana S. M. Batista, Fabíola A. S. Ribeiro, Adelina P. Santos, Luiz O. Faria

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In this work we have prepared nanocomposites made by mixing Poli (vinilidene fluoride) (PVDF), zirconium oxide (ZrO₂) and multi–walled carbon nanotubes (MWCNTs) aiming to find dosimetric properties for applications in high dose dosimetry. The samples were irradiated with a Co-60 source at constant dose rate (16.7 kGy/h), with doses ranging from 100 to 2750 kGy. The UV-Vis and FTIR spectrophotometry have been used to monitor the appearing of C=C conjugated bonds and radio-oxidation of carbon (C=O). FTIR spectrometry has that the absorbance intensities at 1715 cm⁻¹ and 1730 cm⁻¹ can be used for high dosimetry purposes for gamma doses ranging from 500 to 2750 kGy. In this range, it is possible to observe a linear relationship between Abs & Dose. Fading of signal was evaluated for one month and reproducibility in 2000 kGy dose. Scanning Electron Microscopy (SEM) and Energy-dispersive X-ray spectroscopy (EDX) was used for evaluated the dispersion ZrO₂ and MWCNT in the matrix of the PVDF.

Keywords: polymer, composite, high dose dosimetry, PVDF/ZrO₂/MWCNT

Procedia PDF Downloads 276

Authors: Abdul Rehman, Bo Liu

Abstract:

Axial flow turbines are commonly designed with high loads that generate strong secondary flows and result in high secondary losses. These losses contribute to almost 30% to 50% of the total losses. Non-axisymmetric endwall profiling is one of the passive control technique to reduce the secondary flow loss. In this paper, the non-axisymmetric endwall profile construction and optimization for the stator endwalls are presented to improve the efficiency of a high pressure turbine. The commercial code NUMECA Fine/ Design3D coupled with Fine/Turbo was used for the numerical investigation, design of experiments and the optimization. All the flow simulations were conducted by using steady RANS and Spalart-Allmaras as a turbulence model. The non-axisymmetric endwalls of stator hub and shroud were created by using the perturbation law based on Bezier Curves. Each cut having multiple control points was supposed to be created along the virtual streamlines in the blade channel. For the design of experiments, each sample was arbitrarily generated based on values automatically chosen for the control points defined during parameterization. The Optimization was achieved by using two algorithms i.e. the stochastic algorithm and gradient-based algorithm. For the stochastic algorithm, a genetic algorithm based on the artificial neural network was used as an optimization method in order to achieve the global optimum. The evaluation of the successive design iterations was performed using artificial neural network prior to the flow solver. For the second case, the conjugate gradient algorithm with a three dimensional CFD flow solver was used to systematically vary a free-form parameterization of the endwall. This method is efficient and less time to consume as it requires derivative information of the objective function. The objective function was to maximize the isentropic efficiency of the turbine by keeping the mass flow rate as constant. The performance was quantified by using a multi-objective function. Other than these two classifications of the optimization methods, there were four optimizations cases i.e. the hub only, the shroud only, and the combination of hub and shroud. For the fourth case, the shroud endwall was optimized by using the optimized hub endwall geometry. The hub optimization resulted in an increase in the efficiency due to more homogenous inlet conditions for the rotor. The adverse pressure gradient was reduced but the total pressure loss in the vicinity of the hub was increased. The shroud optimization resulted in an increase in efficiency, total pressure loss and entropy were reduced. The combination of hub and shroud did not show overwhelming results which were achieved for the individual cases of the hub and the shroud. This may be caused by fact that there were too many control variables. The fourth case of optimization showed the best result because optimized hub was used as an initial geometry to optimize the shroud. The efficiency was increased more than the individual cases of optimization with a mass flow rate equal to the baseline design of the turbine. The results of artificial neural network and conjugate gradient method were compared.

Keywords: artificial neural network, axial turbine, conjugate gradient method, non-axisymmetric endwall, optimization

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Authors: Ruchi, A. M. Acu, Purshottam N. Agrawal

Abstract:

The purpose of this paper to introduce the Durrmeyer type modification of q-generalized-Bernstein operators which include the Bernstein polynomials in the particular α = 0. We investigate the rate of convergence by means of the Lipschitz class and the Peetre’s K-functional. Also, we define the bivariate case of Durrmeyer type modification of q-generalized-Bernstein operators and study the degree of approximation with the aid of the partial modulus of continuity and the Peetre’s K-functional. Finally, we introduce the GBS (Generalized Boolean Sum) of the Durrmeyer type modification of q- generalized-Bernstein operators and investigate the approximation of the Bögel continuous and Bögel differentiable functions with the aid of the Lipschitz class and the mixed modulus of smoothness.

Keywords: Bögel continuous, Bögel differentiable, generalized Boolean sum, Peetre’s K-functional, Lipschitz class, mixed modulus of smoothness

Procedia PDF Downloads 198

Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

Abstract:

Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: texture classification, texture descriptor, SIFT, SURF, ORB

Procedia PDF Downloads 350