Search results for: crack growth prediction

Authors: Arun Goel

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Prediction of maximum local scour is necessary for the safety and economical design of the bridges. A number of equations have been developed over the years to predict local scour depth using laboratory data and a few pier equations have also been proposed using field data. Most of these equations are empirical in nature as indicated by the past publications. In this paper, attempts have been made to compute local depth of scour around bridge pier in dimensional and non-dimensional form by using linear regression, simple regression and SVM (Poly and Rbf) techniques along with few conventional empirical equations. The outcome of this study suggests that the SVM (Poly and Rbf) based modeling can be employed as an alternate to linear regression, simple regression and the conventional empirical equations in predicting scour depth of bridge piers. The results of present study on the basis of non-dimensional form of bridge pier scour indicates the improvement in the performance of SVM (Poly and Rbf) in comparison to dimensional form of scour.

Keywords: modeling, pier scour, regression, prediction, SVM (Poly and Rbf kernels)

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Authors: Mosima M. Mabitsela

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Groundnut is preferably grown on light textured soils. Most of these light textured soils tend to be highly weathered and characterized by high soil acidity and low nutrient status. One major soil factor associated with infertility of acidic soils that can negatively depress groundnut yield is aluminium (Al) toxicity. In plants Al toxicity damages root cells, leading to inhibition of root growth as a result of the suppression of cell division, cell elongation and cell expansion in the apical meristem cells of the root. The end result is that roots become stunted and brittle, root hair development is poor, and the root apices become swollen. This study was conducted to determine the effects of aluminium (Al) toxicity on a range of groundnut varieties. Fifteen cultivars were tested in incremental aluminum (Al) supply in an ebb and flow solution culture laid out in a randomized complete block design. There were six aluminium (Al) treatments viz. 0 µM, 1 µM, 5.7 µM, 14.14 µM, 53.18 µM, and 200 µM. At 1 µM there was no inhibitory effect on the growth of groundnut. The inhibition of groundnut growth was noticeable from 5.7 µM to 200 µM, where the severe effect of aluminium (Al) stress was observed at 200 µM. The cultivars varied in their response to aluminium (Al) supply in solution culture. Groundnuts are one of the most important food crops in the world, and its supply is on a decline due to the light-textured soils that they thrive under as these soils are acidic and can easily solubilize aluminium (Al) to its toxic form. Consequently, there is a need to develop groundnut cultivars with high tolerance to soil acidity.

Keywords: aluminium toxicity, cultivars, reduction, root growth

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Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar

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Several meteorological parameters were used for the prediction of monthly average daily global solar radiation on horizontal using recurrent neural networks (RNNs). Climatological data and measures, mainly air temperature, humidity, sunshine duration, and wind speed between 1995 and 2007 were used to design and validate a feed forward and recurrent neural network based prediction systems. In this paper we present our reference system based on a feed-forward multilayer perceptron (MLP) as well as the proposed approach based on an RNN model. The obtained results were promising and comparable to those obtained by other existing empirical and neural models. The experimental results showed the advantage of RNNs over simple MLPs when we deal with time series solar radiation predictions based on daily climatological data.

Keywords: recurrent neural networks, global solar radiation, multi-layer perceptron, gradient, root mean square error

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Authors: Stephen Olusanmi Akintayo, Ilesanmi Fadahunsi

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The ability of Lactic acid bacteria (LAB) to grow and survive in milk is being exploited in industrial and biotechnological applications. Although considerable studies have been reported on the fermentation of milk, however, not so much work has been documented on the selection of LAB strains from milk of the Nigerian local cattle breeds for their starter culture potentials. A total of 110 LAB were isolated from raw milk of Sokoto gudali cattle breed. The isolates were screened for their proteolytic activities on skimmed milk media with isolates A07, F06 and A01 showing the highest zone of clearance of 18.5mm, 18.5mm, and 18.0mm respectively and were selected for the studies of their growth in different constituents of milk. A01, F06, and A07 were identified as Pediococcus acidilactici, Lactococcus raffinolactis, and Leuconostoc mesenteriodes respectively using cultural, biochemical, physiological and molecular characterization techniques. Leuconostoc mesenteriodes showed the highest growth in all the milk components that were used in this study. The three LAB species selected showed a growth range of 6.46 log cfu/ml to 10.91 log cfu/ml in lactose with Leuconostoc mesenteriodes showing the highest growth of 10.91 log cfu/ml while Pediococcus acidilactici recorded the lowest growth of 9.78 log cfu/ml. In medium containing leucine as the only amino acid, the viable counts of Pediococcus acidilactici, Lactococcus raffinolactis and Leuconostoc mesenteriodes in log cfu/ml at zero hour were 6.39, 6.36 and 6.38 respectively which increased to 9.31 log cfu/ml, 9.21 log cfu/ml, 9.92 log cfu/ml respectively after 24 hours. Similarly, in all other substrates (casein, lysine, glutamic acid, aspartic acid, stearic acid and oleic acid ) tested in this study, Leuconostoc mesenteriodes showed the highest growth. It was observed that the highest quantity of lactic acid (15.31mg/ml) was produced by Leuconostoc mesenteriodes. The same trend was also observed in the production of diacetyl and hydrogen peroxide by the three tested microorganisms. Due to its ability to grow maximally in milk components, Leuconostoc mesenteriodes shows potential as starter culture for milk fermentation.

Keywords: Leuconostoc mesenteriodes, lactic acid bacteria, Sokoto gudali, starter culture

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Authors: Mohamed Yusuf

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Aim: The growth promoting the effect of the blue-green filamentous alga Spirulina platensis (SP) was observed on meat type Japanese quail with antibiotic growth promoter alternative and immune enhancing power. Materials and Methods: This study was conducted on 180 Japanese quail chicks for 4 weeks to find out the effect of diet type (vegetarian protein diet [VPD] and fish meal protein diet [FMPD])- Spirulina dose interaction (1 or 2 g/kg diet) on growth performance, gut microbiota, and sensory meat quality of growing Japanese quails (1-5 weeks old). Results: Data revealed improvement (p<0.05) of weight gain, feed conversion ratio, and European efficiency index due to 1, 2 g (SP)/kg VPD, and 2 g (SP)/kg FMPD, respectively. There was a significant decrease of ileum mean pH value by 1 g(SP)/kg VPD. Concerning gut microbiota, there was a trend toward an increase in Lactobacilli count in both 1; 2 g (SP)/kgVPD and 2 g (SP)/kg FMPD. It was concluded that 1 or 2 g (SP)/kg vegetarian diet may enhance parameters of performance without obvious effect on both meat quality and gut microbiota. Moreover, 1 and/or 2 g (SP) may not be invited to share fishmeal based diet for growing Japanese quails. Conclusion: Using of SP will support the profitable production of Japanese quails fed vegetable protein diet.

Keywords: isocaloric, isonitrogenous, meat quality, performances, quails, spirulina, spirulina

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Authors: Seongjun Kim, Sanghoon Shim, Jinwooung Kim, Jaehwan Jung, Sung-Ah Kim

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As the development of information and communication technology, the convergence of machine learning of the ICT area and design is attempted. In this way, it is possible to grasp the correlation between various design elements, which was difficult to grasp, and to reflect this in the design result. In architecture, there is an attempt to predict the performance, which is difficult to grasp in the past, by finding the correlation among multiple factors mainly through machine learning. In architectural design area, some attempts to predict the performance affected by various factors have been tried. With machine learning, it is possible to quickly predict performance. The aim of this study is to propose a model that predicts performance according to the block arrangement of apartment housing through machine learning and the design alternative which satisfies the performance such as the daylight hours in the most similar form to the alternative proposed by the designer. Through this study, a designer can proceed with the design considering various design alternatives and accurate performances quickly from the early design stage.

Keywords: apartment housing, machine learning, multi-objective optimization, performance prediction

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Authors: Ju-Hyung Kim, Dae-Ho Mun, Hong-Gun Park

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When an impact is applied to a floating floor, noise and vibration response of high-frequency range is reduced effectively, while amplifies the response at low-frequency range. This means floating floor can make worse noise condition when heavy-weight impact is applied. The amplified response is the result of interaction between finishing layer (mortar plate) and concrete slab. Because an impact force is not directly delivered to concrete slab, the impact force waveform or spectrum can be changed. In this paper, the changed impact spectrum was derived from several floating floor vibration tests. Based on the measured data, numerical modeling can describe the floating floor response, especially at low-frequency range. As a result, heavy-weight impact noise can be predicted using modified impact spectrum.

Keywords: floating floor, heavy-weight impact, prediction, vibration

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Authors: J. Ticona Chambi, E. A. De Almeida, C. A. Andrade Raymundo Gaiotto, A. M. Do Espírito Santo, L. Infantes, S. L. Cuffini

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The solubility of active pharmaceutical ingredients (APIs) is challenging for the pharmaceutical industry. The new multicomponent crystalline forms as cocrystal and solvates present an opportunity to improve the solubility of APIs. Commonly, the procedure to obtain multicomponent crystalline forms of a drug starts by screening the drug molecule with the different coformers/solvents. However, it is necessary to develop methods to obtain multicomponent forms in an efficient way and with the least possible environmental impact. The Hansen Solubility Parameters (HSPs) is considered a tool to obtain theoretical knowledge of the solubility of the target compound in the chosen solvent. H-Bond Propensity (HBP), Molecular Complementarity (MC), Coordination Values (CV) are tools used for statistical prediction of cocrystals developed by the Cambridge Crystallographic Data Center (CCDC). The HSPs and the CCDC tools are based on inter- and intra-molecular interactions. The curcumin (Cur), target molecule, is commonly used as an anti‐inflammatory. The demethoxycurcumin (Demcur) and bisdemethoxycurcumin (Bisdcur) are natural analogues of Cur from turmeric. Those target molecules have differences in their solubilities. In this way, the work aimed to analyze and compare different tools for multicomponent forms prediction (solvates) of Cur, Demcur and Biscur. The HSP values were calculated for Cur, Demcur, and Biscur using the chemical group contribution methods and the statistical optimization from experimental data. The HSPmol software was used. From the HSPs of the target molecules and fifty solvents (listed in the HSP books), the relative energy difference (RED) was determined. The probability of the target molecules would be interacting with the solvent molecule was determined using the CCDC tools. A dataset of fifty molecules of different organic solvents was ranked for each prediction method and by a consensus ranking of different combinations: HSP, CV, HBP and MC values. Based on the prediction, 15 solvents were selected as Dimethyl Sulfoxide (DMSO), Tetrahydrofuran (THF), Acetonitrile (ACN), 1,4-Dioxane (DOX) and others. In a starting analysis, the slow evaporation technique from 50°C at room temperature and 4°C was used to obtain solvates. The single crystals were collected by using a Bruker D8 Venture diffractometer, detector Photon100. The data processing and crystal structure determination were performed using APEX3 and Olex2-1.5 software. According to the results, the HSPs (theoretical and optimized) and the Hansen solubility sphere for Cur, Demcur and Biscur were obtained. With respect to prediction analyses, a way to evaluate the predicting method was through the ranking and the consensus ranking position of solvates already reported in the literature. It was observed that the combination of HSP-CV obtained the best results when compared to the other methods. Furthermore, as a result of solvent selected, six new solvates, Cur-DOX, Cur-DMSO, Bicur-DOX, Bircur-THF, Demcur-DOX, Demcur-ACN and a new Biscur hydrate, were obtained. Crystal structures were determined for Cur-DOX, Biscur-DOX, Demcur-DOX and Bicur-Water. Moreover, the unit-cell parameter information for Cur-DMSO, Biscur-THF and Demcur-ACN were obtained. The preliminary results showed that the prediction method is showing a promising strategy to evaluate the possibility of forming multicomponent. It is currently working on obtaining multicomponent single crystals.

Keywords: curcumin, HSPs, prediction, solvates, solubility

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Authors: Ashish Kumar, Tejendra Dixit, I. A. Palani, Vipul Singh

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Zinc oxide, with its interesting properties such as large band gap (3.37eV), high exciton binding energy (60 meV) and intense UV absorption has been studied in literature for various applications viz. optoelectronics, biosensors, UV-photodetectors etc. The performance of ZnO devices is highly influenced by morphologies, size, crystallinity of the ZnO active layer and processing conditions. Recently, our group has shown the influence of the in situ addition of KMnO4 in the precursor solution during the hydrothermal growth of ZnO nanorods (NRs) on their near band edge (NBE) emission. In this paper, we have investigated the effect of post-growth annealing on the variations in NBE and deep level (DL) emissions of as grown ZnO nanorods. These observed results have been explained on the basis of X-ray Diffraction (XRD) and Raman spectroscopic analysis, which clearly show that improved crystalinity and quantum confinement in ZnO nanorods.

Keywords: ZnO, nanorods, hydrothermal, KMnO4

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Authors: Jung-Il Kang, Jeon Eon Park, Yu-Jin Moon, Young-Seok Ahn, Eun-Sook Yoo, Hee-Kyoung Kang

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This study was conducted to evaluate the effect of Undariopsis peterseniana, a seaweed native to Jeju Island, Korea, on the growth of hair. The dermal papilla cells (DPCs) have known to regulate hair growth cycle and length of hair follicle through interact with epithelial cells. When immortalized vibrissa DPCs were treated with the U. peterseniana extract, the U. peterseniana extract significantly increased the proliferation of DPCs. The effect of U. peterseniana extract on the growth of vibrissa follicles was also examined. U. peterseniana extract significantly increased the hair-fiber lengths of the vibrissa follicles. Hair loss is partly caused by dihydrotestosterone (DHT) binding to androgen receptor in hair follicles, and the inhibition of 5α-reductase activity can prevent hair loss through the decrease of DHT level. The U. peterseniana extract inhibited 5α-reductase activity. Minoxidil, a potent hair-growth agent, can induce proliferation in NIH3T3 fibroblasts by opening KATP channels. We thus examined the proliferative effects of U. peterseniana extract in NIH3T3 fibroblasts. U. peterseniana extract significantly increased the proliferation of NIH3T3 fibroblasts. Tetraethylammonium chloride (TEA), a K+ channel blocker, inhibited U. peterseniana-induced proliferation in NIH3T3 fibroblasts. These results suggest that U. peterseniana could have the potential to treat alopecia through the proliferation of DPCs, the inhibition of 5α-reductase activity and the opening of KATP channels. [Acknowledgement] This research was supported by The Leading Human Resource Training Program of Regional Neo industry through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and future Planning (2016H1D5A1908786).

Keywords: hair growth, Undariopsis peterseniana, vibrissa follicles, dermal papilla cells, 5α-reductase, KATP channels

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Authors: Malgorzata Rudnicka, Waldemar Karcz

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Introduction: Naphthoquinones are widely occurring organic compounds produced by bacteria, fungi, and plants. They can act as the functional components of biochemical systems (plastoquinone) as well as biologically active substances, which have a negative impact on environmental processes. Naphthoquinones seem to act through two mechanisms: a covalent modification of biological molecules at their nucleophilic sites or by generation of reactive oxygen species (ROS) connected with redox cycling. Investigating the effect of naphthoquinones (1,4-naphthoquinone, lawsone and naphthazarin) on the elongation growth, membrane potential and the level of oxidative stress of maize cells seems to be important due to the possibility of using these substances as herbicides. Methods: All experiments were performed on etiolated maize coleoptile segments. Simultaneous measurements of elongation growth and pH of the incubation medium were carried out using an angular position transducer, allowing a precise record of the growth kinetics. To compare the oxidative stress level induced by all tested naphthoquinones, the changes in malondialdehyde content, as well as superoxide dismutase and catalase activities were measured. In order to measure the membrane potential of parenchymal cells the standard electrophysiology technique was used. Results: Naphthoquinones such as: 1,4-naphthoquinone, lawsone and naphthazarin were studied. It was found that all of the naphthoquinones diminished the growth of the maize coleoptile cells depending on the type of naphthoquinones and their concentration. Interestingly, naphthazarin at the intermediate concentration was less toxic compared to the others. In addition, the effect of naphthoquinones on the oxidative stress was dependent on their concentration as well. Superoxide dismutase and catalase activities were changed in the presence of higher concentrations of naphthoquinones. Similar interrelations were observed for membrane potential changes. Conclusion: It can be concluded that naphthoquinones tested differ in their toxic effect on the growth of maize coleoptile cells. Furthermore, naphthoquinones can be distinguish considering the oxidative stress level and membrane potential changes. The results presented here give new insight into the possible opportunities of practical usage of naphthoquinones for herbicides improvement.

Keywords: growth rate, membrane potential, naphthoquinones, oxidative stress

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Authors: Ahmed T. Farid, Muhammed Rizwan

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Geotechnical study for evaluating soil or rock permeability is a highly important parameter. Permeability values for rock formations are more difficult for determination than soil formation as it is an effect of the rock quality and its fracture values. In this research, the prediction of in situ permeability of limestone rock formations was predicted. The limestone rock permeability was evaluated using Lugeon tests (in-situ packer permeability). Different sites which spread all over the Riyadh region of Saudi Arabia were chosen to conduct our study of predicting the in-situ permeability of limestone rock. Correlations were deducted between the values of in-situ permeability of the limestone rock with the value of the rock quality designation (RQD) calculated during the execution of the boreholes of the study areas. The study was performed for different ranges of RQD values measured during drilling of the sites boreholes. The developed correlations are recommended for the onsite determination of the in-situ permeability of limestone rock only. For the other sedimentary formations of rock, more studies are needed for predicting the actual correlations related to each type.

Keywords: In situ, packer, permeability, rock, quality

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Authors: Agustine Melviana, Rizkita Esyanti

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Stevia plant contains steviol glycosides which is estimated to be 300 times sweeter than sucrose. However in Indonesia, conventional (in vivo) propagation of Stevia rebaudiana was not effective due to a poor result. Therefore, alternative methods to propagate S. rebaudiana plants is needed, one of it is using in vitro method. Multiplication with a large quantity of stevia biomass in relatively short period can be conducted by using TIS RITA® (Recipient for Automated Temporary Immersion System). The objective of this study was to evaluate the effect of immersion period of the medium on growth and the medium bioconversion into the production of shoot biomass. The study was conducted to determine the effect of different intensity period of medium to enhance biomass of stevia shoots. Shoot culture of S. rebaudiana was grown in full strength MS medium supplemented with 1 ppm Kinetin. RITA® bioreactors were set up with two different immersion periods, 15 min (RITA® 15) and 30 min (RITA® 30), scheduled every 6 hours and incubated for 21 days. The result indicated that immersion period affected the biomass and growth rate (µ). Thirty-minutes immersion showed greater percentage of shoot multiplication (93.44 ± 0.83%), percentage of leaf growth (85.24 ± 5.99%), growth rate (0.042 ± 0.001 g/day), and productivity (0.066 g/L medium/day) compared to that immersed in RITA® 15 min (76.90 ± 4.85%; 79.73 ± 7.76; 0.045 ± 0.004 g/day, and 0.045 g/L medium/day respectively). Enhancement of biomass in RITA® 30 reached 1,702 ± 0,114 gr, whereas in RITA® 15 only 0,953 ± 0,093 gr. Additionally, the pattern of sucrose, mineral, and inorganic compounds consumption followed the growth of plant biomass for both systems. In conclusion, the bioconversion efficiency from medium to biomass in RITA® 30 is better than RITA® 15.

Keywords: intensity period, shoot culture, Stevia rebaudiana, TIS RITA®

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Authors: Perpetua Modjadji, Sphiwe Madiba

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Background: The growth patterns of children are good nutritional indicators of their nutritional status, health, and socioeconomic level. However, the maternal factors and the belief system of the society affect the growth of children promoting undernutrition. This study determined the influence of maternal factors on growth patterns of schoolchildren in a rural site. Methods: A convergent mixed method study was conducted among 508 schoolchildren and their mothers in Dikgale Health and Demographic Surveillance System Site, South Africa. Multistage sampling was used to select schools (purposive) and learners (random), who were paired with their mothers. Anthropometry was measured and socio-demographic, obstetrical, household information, maternal influence on children’s nutrition, and growth were assessed using an interviewer administered questionnaire (quantitative). The influence of the cultural beliefs and practices of mothers on the nutrition and growth of their children was explored using focus group discussions (qualitative). Narratives of mothers were used to best understand growth patterns of schoolchildren (mixed method). Data were analyzed using STATA 14 (quantitative) and Nvivo 11 (qualitative). Quantitative and qualitative data were merged for integrated mixed method analysis using a joint display analysis. Results: Mean age of children was 10 ± 2 years, ranging from 6 to 15 years. Substantial percentages of thinness (25%), underweight (24%), and stunting (22%) were observed among the children. Mothers had a mean age of 37 ± 7 years, and 75% were overweight or obese. A depressed socio-economic status indicated by a higher rate of unemployment with no income (82.3%), and dependency on social grants (86.8%) was observed. Determinants of poor growth patterns were child’s age and gender, maternal age, height and BMI, access to water supply, and refrigerator use. The narratives of mothers suggested that the children in most of their households were exposed to poverty and the inadequate intake of quality food. Conclusion: Poor growth patterns were observed among schoolchildren while their mothers were overweight or obese. Child’s gender, school grade, maternal body mass index, and access to water were the main determinants. Congruence was observed between most qualitative themes and quantitative constructs. A need for a multi sectoral approach considering an evidence based and feasible nutrition programs for schoolchildren, especially those in rural settings and educating mothers, cannot be over-emphasized.

Keywords: growth patterns, maternal factors, rural context, schoolchildren, South Africa

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Authors: Nesrine Bouguerra

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Entrepreneurship is seen as a necessary ingredient for stimulating economic growth and employment opportunities in all societies. SMEs account for a wide share of economic activity and development. they are the primary engine of job creation, income growth and poverty reduction. Indeed, government support for entrepreneurship is a strategic option to foster economic growth and females’ input in this regard, is of equal significance not only for employability and productivity but also to narrow the gender gap created by social attitudes and beliefs. This study investigates the impact of socio–cultural factors, among other barriers on female entrepreneurial intention in Algeria. Data will be collected using a mixed method approach (Questionnaires and Interviews) from women intending to become entrepreneurs and those already in the field. This study has conceptual, theoretical and empirical contributions to the field of entrepreneurship which will be unveiled throughout.

Keywords: female entrepreneurship, SMEs, women, socio –cultural values, barriers

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Authors: Hilya Mudrika Arini, Nur Aini Masruroh, Budi Hartono

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There are more than 20 terrorist threats from 2002 to 2012 in Indonesia. Despite of this fact, preventive solution through studies in the field of national security in Indonesia has not been conducted comprehensively. This study aims to provide a preventive solution by developing prediction model of the terrorist threat in Indonesia by using Bayesian network. There are eight stages to build the model, started from literature review, build and verify Bayesian belief network to what-if scenario. In order to build the model, four experts from different perspectives are utilized. This study finds several significant findings. First, news and the readiness of terrorist group are the most influent factor. Second, according to several scenarios of the news portion, it can be concluded that the higher positive news proportion, the higher probability of terrorist threat will occur. Therefore, the preventive solution to reduce the terrorist threat in Indonesia based on the model is by keeping the positive news portion to a maximum of 38%.

Keywords: Bayesian network, decision analysis, national security system, text mining

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Authors: Chih-Hsin Lin, Shyh-Yuan Lee, Yuan-Min Lin

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For many tissue engineering applications, an important goal is to create functional tissues in-vitro, and such tissues to be viable, they have to be vascularized. Endothelial cells (EC) and endothelial progenitor cells (EPC) are promising candidates for vascularization. However, both of them have limited expansion capacity and autologous cells currently do not exist for either ECs or EPCs. Therefore, we use bone marrow mesenchymal stem cells (MSC) as a source material for ECs. Growth supplements are commonly used to induce MSC differentiation, and further improvements in differentiation conditions can be made by modifying the cell's growth environment. An example is pre-treatment of the growth dish with gas plasma, in order to modify the surface functional groups of the material that the cells are seeded on. In this work, we compare the effects of different gas plasmas on the growth and differentiation of MSCs. We treat the dish with different plasmas (CO2, N2, and O2) and then induce MSC differentiation with endothelial growth medium-2 (EGM-2). We find that EGM-2 by itself upregulates EC marker CD31 mRNA expression, but not VEGFR2, CD34, or vWF. However, these additional EC marker expressions were increased for cells seeded on plasma treated substrates. Specifically, for EC markers, we found that N2 plasma treatment upregulated CD31 and VEGFR-2 mRNA expressions; CO2 plasma treatment upregulated CD34 and vWF mRNA expressions. The osteogenic markers ALP and osteopontin mRNA expressions were markedly enhanced on all plasma-treated dishes. We also found that plasma treatment in conjunction with EGM-2 growth medium can enhance MSCs differentiation into endothelial-like cells and osteogenic-like cells. Our work shows that the effect of the growth medium (EGM-2) on MSCs differentiation is influenced by the plasma modified surface chemistry of the substrate. In conclusion, plasma surface modification can enhance EGM-2 effectiveness and induced both endothelial and osteogenic differentiation. Our findings provide a method to enhance EGM-2 based cell differentiation, with consequences for tissue engineering and stem cell biology applications.

Keywords: endothelial differentiation, EGM-2, osteogenesis, plasma treatment, surface modification

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Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

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Authors: Vahid Nourani, Atefeh Ashrafi

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Prediction of treated wastewater quality is a matter of growing importance in water treatment procedure. In this way artificial neural network (ANN), as a robust data-driven approach, has been widely used for forecasting the effluent quality of wastewater treatment. However, developing ANN model based on appropriate input variables is a major concern due to the numerous parameters which are collected from treatment process and the number of them are increasing in the light of electronic sensors development. Various studies have been conducted, using different clustering methods, in order to classify most related and effective input variables. This issue has been overlooked in the selecting dominant input variables among wastewater treatment parameters which could effectively lead to more accurate prediction of water quality. In the presented study two ANN models were developed with the aim of forecasting effluent quality of Tabriz city’s wastewater treatment plant. Biochemical oxygen demand (BOD) was utilized to determine water quality as a target parameter. Model A used Principal Component Analysis (PCA) for input selection as a linear variance-based clustering method. Model B used those variables identified by the mutual information (MI) measure. Therefore, the optimal ANN structure when the result of model B compared with model A showed up to 15% percent increment in Determination Coefficient (DC). Thus, this study highlights the advantage of PCA method in selecting dominant input variables for ANN modeling of wastewater plant efficiency performance.

Keywords: Artificial Neural Networks, biochemical oxygen demand, principal component analysis, mutual information, Tabriz wastewater treatment plant, wastewater treatment plant

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Authors: Hamidou Diallo, Marianne Guille

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This paper identifies leading triggers of deficient episodes in terms of GDP growth based on a sample of countries at different stages of development over 1994-2017. Using logit models, we build early warning systems (EWS), and our results show important differences between developing countries (DCs) and advanced economies (AEs). For AEs, the main predictors of the probability of entering in a GDP growth deficient episode are the deterioration of external imbalances and the vulnerability of fiscal position while DCs face different challenges that need to be considered. The key indicators for them are first, the low ability to pay their debts, and second, their belonging or not to a common currency area. We also build homogeneous pools of countries inside AEs and DCs. The evolution of the proportion of AE countries in the riskiest pool is marked first, by three distinct peaks just after the high-tech bubble burst, the global financial crisis, and the European sovereign debt crisis, and second by a very low minimum level in 2006 and 2007. In contrast, the situation of DCs is characterized first by the relative stability of this proportion and then by an upward trend from 2006, that can be explained by a more unfavorable socio-political environment leading to shortcomings in the fiscal consolidation.

Keywords: currency area, early warning system, external imbalances, fiscal vulnerability, GDP growth, public debt

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Authors: A. L. R. Rangel, J. A. M. Chaves, A. P. R. Alves Claro

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Surface modification of titanium and its alloys using TiO2 nanotube growth has been widely studied for biomedical field due to excellent interaction between implant and biological environment. The success of this treatment is directly related to anatase phase formation (TiO2 phase) which affects the cells growth. The aim of this study was to evaluate the phases formed in the nanotubes growth on the Ti-15Mo surface. Nanotubes were grown by electrochemical anodization of the alloy in ammonium fluoride based glycerol electrolyte for 24 hours at 20V. Then, the samples were annealed at 200°,400°, 450°, 500°, 600°, and 800° C for 1 hour. Contact angles measurements, scanning electron microscopy images and X rays diffraction analysis (XRD) were carried out for all samples. Raman Spectroscopy was used to evaluate TiO2 phases transformation in nanotubes samples as well. The results of XRD showed anatase formation for lower temperatures, while at 800 ° C the rutile phase was observed all over the surface. Raman spectra indicate that this phase transition occurs between 500 and 600 °C. The different phases formed have influenced the nanotubes morphologies, since higher annealing temperatures induced agglutination of the TiO2 layer, disrupting the tubular structure. On the other hand, the nanotubes drastically reduced the contact angle, regardless the annealing temperature.

Keywords: nanotubes, TiO2, titanium alloys, Ti-15Mo

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Authors: Mehdi Habibagahi, Shami Nejadi, Ata Aminfar

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A significant degradation factor that impacts the durability of concrete structures is the alkali-silica reaction. Engineers are frequently charged with the challenges of conducting a thorough safety assessment of concrete structures that have been impacted by ASR. The alkali-silica reaction has a major influence on the structural capacities of structures. In most cases, the reduction in compressive strength, tensile strength, and modulus of elasticity is expressed as a function of free expansion and crack widths. Predicting the effect of ASR on flexural strength is also relevant. In this paper, a nonlinear three-dimensional (3D) finite-element model was proposed to describe the flexural strength degradation induced byASR.Initial strains, initial stresses, initial cracks, and deterioration of material characteristics were all considered ASR factors in this model. The effects of ASR on structural performance were evaluated by focusing on initial flexural stiffness, force–deformation curve, and load-carrying capacity. Degradation of concrete mechanical properties was correlated with ASR growth using material test data conducted at Tech Lab, UTS, and implemented into the FEM for various expansions. The finite element study revealed a better understanding of the ASR-affected RC beam's failure mechanism and capacity reduction as a function of ASR expansion. Furthermore, in this study, decreasing of the residual mechanical properties due to ASRisreviewed, using as input data for the FEM model. Finally, analysis techniques and a comparison of the analysis and the experiment results are discussed. Verification is also provided through analyses of reinforced concrete beams with behavior governed by either flexural or shear mechanisms.

Keywords: alkali-silica reaction, analysis, assessment, finite element, nonlinear analysis, reinforced concrete

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Authors: Rachel Y. Zhang, Christopher K. Anderson

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A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

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Authors: Mohammed Yagoub

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The new orientation to the market economy sponsored by the Algeria government in the early Nineties of the last century, and its desire to develop investment mechanisms and the promotion of development recently, the access into a partnership with the European Union, and the forthcoming accession to the World Trade Organization, foreign direct investment makes one of the most important means of opening up to foreign markets and bring technology and interact with globalization, this article we will discuss the impact of FDI on economic growth in the Algerian.

Keywords: economic, development, markets, FDI, displacement, globalization

Procedia PDF Downloads 338

Authors: Merry Muspita Dyah Utami

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The positive effect of garlic extract have been reported by many studies. It has antibiotical potential, antibacterial, antiviral, antiparasitic, antifungal, and growth promoting. Supplementary garlic for broilers could mediate in getting the bioactive compounds in garlic. The avian bursa must be essential for antibody-mediated immunity. The size of bursa of fabricius must be some sort of endocrine or lymphoid gland associated with growth and sexual development. The research was conducted to evaluate the effects of garlic extract on growth performance and immune system of broiler. Seventy-two day old chick were equally divided into four group, three replication and six chicks each. Group I was control without garlic extract, then garlic extraxt was administrated to the experimental group II, III and IV (2, 4, 6% in ration). The experiment was conducted for three weeks period from day old chick to 21 days. Body weight of broiler were determined at day 1 and 21, feed intake was determined at the same period, feed conversion ratio was calculated accordingly. At 21 day age, four birds per replicate were slaughtered , bursa was collected, weight and calculated as a percentage of live body weight. Mortality was recorded as it occurred and was used to ajust the total number of broiler to determine the total feed intake and feed conversion rasio. Data were expressed as the mean was compare by one way analysis of variance (Anova) follow by Duncan Test, which used to identify differences between groups. A value of P<0.05 was accepted as significance. The body weight, feed conversion rasio, and the weight of bursa of fabricius showed a significant differences, but feed consumption and the percentage of bursa of live body weight were not significantly different (P > 0.05) influenced by dietary treatments. The results of this research, garlic extract has a potential role as natural growth promoter and immunomodulatory system in broiler.

Keywords: garlic extract, growth, immunity, broiler

Procedia PDF Downloads 310

Authors: Jawairia Umar, Tanveer Hussain, Zulfiqar Ali, Muhammad Maqsood

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Different knitted structures and knitted parameters play a vital role in the stretch and recovery management of compression sportswear in addition to the materials use to generate this stretch and recovery behavior of the fabric. The present work was planned to predict the different performance indicators of a compression sportswear fabric with some ground parameters i.e. base yarn stitch length (polyester as base yarn and spandex as plating yarn involve to make a compression fabric) and linear density of the spandex which is a key material of any sportswear fabric. The prediction models were generated by response surface method for performance indicators such as stretch & recovery percentage, compression generated by the garment on body, total elongation on application of high power force and load generated on certain percentage extension in fabric. Certain physical properties of the fabric were also modeled using these two parameters.

Keywords: Compression, sportswear, stretch and recovery, statistical model, kikuhime

Procedia PDF Downloads 362

Authors: Eun-Taek Sin, Hyun-Ju Jang, Chang Geun Song, Yong-Sik Han

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Due to the climate change, the coastal urban area repeatedly suffers from the loss of property and life by flooding. There are three main causes of inland submergence. First, when heavy rain with high intensity occurs, the water quantity in inland cannot be drained into rivers by increase in impervious surface of the land development and defect of the pump, storm sewer. Second, river inundation occurs then water surface level surpasses the top of levee. Finally, Coastal inundation occurs due to rising sea water. However, previous studies ignored the complex mechanism of flooding, and showed discrepancy and inadequacy due to linear summation of each analysis result. In this study, inland flooding and river inundation were analyzed together by HDM-2D model. Petrov-Galerkin stabilizing method and flux-blocking algorithm were applied to simulate the inland flooding. In addition, sink/source terms with exponentially growth rate attribute were added to the shallow water equations to include the inland flooding analysis module. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. To consider the coastal surge, another module was developed by adding seawater to the existing Inland Flooding-River Inundation binding module for comprehensive flooding analysis. Based on the combined modules, the Coastal Inundation – Inland & River Flow Interface was simulated by inputting the flow rate and depth data in artificial flume. Accordingly, it was able to analyze the flood patterns of coastal cities over time. This study is expected to help identify the complex causes of flooding in coastal areas where complex flooding occurs, and assist in analyzing damage to coastal cities. Acknowledgements—This research was supported by a grant ‘Development of the Evaluation Technology for Complex Causes of Inundation Vulnerability and the Response Plans in Coastal Urban Areas for Adaptation to Climate Change’ [MPSS-NH-2015-77] from the Natural Hazard Mitigation Research Group, Ministry of Public Safety and Security of Korea.

Keywords: flooding analysis, river inundation, inland flooding, 2D hydrodynamic model

Procedia PDF Downloads 345

Authors: Gabriel S. De Oliveira, Patricia P. Adriani, Christophe Moriseau, Bruce D. Hammock, Felipe S. Chambergo

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Epoxide hydrolases (EHs) are enzymes that are present in all living organisms and catalyze the hydrolysis of epoxides to the corresponding vicinal diols. EHs have high biotechnological interest for the drug design and chemistry transformation for industries. In this study, we describe the identification of substrates and inhibitors of epoxide hydrolase enzyme from the filamentous fungus Trichoderma reesei (TrEH), and these inhibitors showed the fungal growth inhibitory activity. We have used the cloned enzyme and expressed in E. coli to develop the screening in the library of fluorescent substrates with the objective of finding the best substrate to be used in the identification of good inhibitors for the enzyme TrEH. The substrate (3-phenyloxiranyl)-acetic acid cyano-(6-methoxy-naphthalen-2-yl)-methyl ester showed the highest specific activity and was chosen for the next steps of the study. The inhibitors screening was performed in the library with more than three thousand molecules and we could identify the 6 best inhibitors. The IC50 of these molecules were determined in nM and all the best inhibitors have urea or amide in their structure, because It has been recognized that these groups fit well in the hydrolase catalytic pocket of the epoxide hydrolases. Then the growth of T. reesei in PDA medium containing these TrEH inhibitors was tested, and fungal growth inhibition activity was demonstrated with more than 60% of inhibition of fungus growth in the assay with the TrEH inhibitor with the lowest IC50. Understanding how this EH enzyme from T. reesei responds to inhibitors may contribute for the study of fungal metabolism and drug design against pathogenic fungi.

Keywords: epoxide hydrolases, fungal growth inhibition, inhibitor, Trichoderma reesei

Procedia PDF Downloads 183

Authors: H. Pasternak, A. Chwastek

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The paper describes the results from a research project about repair of welds. The repair was carried out by grinding the flawed seams and re-welding them. The main task was to determine the FAT classes of original state and after repair of seams according to the assessment procedures, such as nominal, structural and effective notch stress approach. The first part shows the results of the tests, the second part encloses numerical analysis and evaluation of results to determine the fatigue strength classes according to three assessment procedures.

Keywords: cyclic loading, fatigue crack, post-weld treatment, seams’ repair

Procedia PDF Downloads 243

Authors: Wendu Pang, Yaxin Luo, Junhong Li, Yu Zhao, Danni Cheng, Yufang Rao, Minzi Mao, Ke Qiu, Yijun Dong, Fei Chen, Jun Liu, Jian Zou, Haiyang Wang, Wei Xu, Jianjun Ren

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We aimed to compare the prognostic prediction value of positive lymph node number (PLNN) to the American Joint Committee on Cancer (AJCC) tumor, lymph node, and metastasis (TNM) staging system for patients with hypopharyngeal squamous cell carcinoma (HPSCC). A total of 826 patients with HPSCC from the Surveillance, Epidemiology, and End Results database (2004–2015) were identified and split into two independent cohorts: training (n=461) and validation (n=365). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic effects of PLNN in patients with HPSCC. We further applied six Cox regression models to compare the survival predictive values of the PLNN and AJCC TNM staging system. PLNN showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (P < 0.001) in both univariate and multivariable analyses, and was divided into three groups (PLNN 0, PLNN 1-5, and PLNN>5). In the training cohort, multivariate analysis revealed that the increased PLNN of HPSCC gave rise to significantly poor OS and CSS after adjusting for age, sex, tumor size, and cancer stage; this trend was also verified by the validation cohort. Additionally, the survival model incorporating a composite of PLNN and TNM classification (C-index, 0.705, 0.734) performed better than the PLNN and AJCC TNM models. PLNN can serve as a powerful survival predictor for patients with HPSCC and is a surrogate supplement for cancer staging systems.

Keywords: hypopharyngeal squamous cell carcinoma, positive lymph nodes number, prognosis, prediction models, survival predictive values

Procedia PDF Downloads 126