Search results for: in vitro skin model

Authors: Lei Zhu, Nan Li

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Cold stamping has been widely applied in the automotive industry for the mass production of a great range of automotive panels. Predicting the springback to ensure the dimensional accuracy of the cold-stamped components is a critical step. The main approaches for the prediction and compensation of springback in cold stamping include running Finite Element (FE) simulations and conducting experiments, which require forming process expertise and can be time-consuming and expensive for the design of cold stamping tools. Machine learning technologies have been proven and successfully applied in learning complex system behaviours using presentative samples. These technologies exhibit the promising potential to be used as supporting design tools for metal forming technologies. This study, for the first time, presents a novel application of a Convolutional Neural Network (CNN) based surrogate model to predict the springback fields for variable U-shape cold bending geometries. A dataset is created based on the U-shape cold bending geometries and the corresponding FE simulations results. The dataset is then applied to train the CNN surrogate model. The result shows that the surrogate model can achieve near indistinguishable full-field predictions in real-time when compared with the FE simulation results. The application of CNN in efficient springback prediction can be adopted in industrial settings to aid both conceptual and final component designs for designers without having manufacturing knowledge.

Keywords: springback, cold stamping, convolutional neural networks, machine learning

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Authors: Jixiang Zhang

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A dynamic of Bertrand duopoly game is analyzed, where players use different production methods and choose their prices with bounded rationality. The equilibriums of the corresponding discrete dynamical systems are investigated. The stability conditions of Nash equilibrium under a local adjustment process are studied. The stability conditions of Nash equilibrium under a local adjustment process are studied. The stability of Nash equilibrium, as some parameters of the model are varied, gives rise to complex dynamics such as cycles of higher order and chaos. On this basis, we discover that an increase of adjustment speed of bounded rational player can make Bertrand market sink into the chaotic state. Finally, the complex dynamics, bifurcations and chaos are displayed by numerical simulation.

Keywords: Bertrand duopoly model, discrete dynamical system, heterogeneous expectations, nash equilibrium

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Authors: Mhuji Kilonzo, Patrick Ndakidemi, Musa Chacha

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Objective: To evaluate antibacterial activity from four selected medicinal plants namely Mystroxylon aethiopicum, Lonchocarpus capassa, Albizia anthelmentica and Myrica salicifolia used for management of bacterial infection in Tanzania. Methods: Minimum Inhibitory Concentration (MIC) of plants extracts against the tested bacterial species was determined by using 96 wells microdilution method. In this method, 50 μL of nutrient broth were loaded in each well followed by 50 μL of extract (100 mg/mL) to make a final volume of 100 μL. Subsequently, 50 μL were transferred from first rows of each well to the second rows and the process was repeated down the columns to the last wells from which 50 μL were discarded. Thereafter, 50 μL of the selected bacterial suspension were added to each well thus making a final volume of 100 μL. The lowest concentration which showed no bacterial growth was considered as MIC. Results: It was revealed that L. capassa leaf ethyl acetate extract exhibited antibacterial activity against Salmonella kisarawe and Salmonella typhi with MIC values of 0.39 and 0.781 mg/mL respectively. Likewise, L. capassa root bark ethyl acetate extracts inhibited growth of S. typhi and E. coli with MIC values of 0.39 and 0.781 mg/mL respectively. The M. aethiopicum leaf and root bark chloroform extracts displayed antibacterial activity against S. kisarawe and S. typhi respectively with MIC value of 0.781 mg/mL. The M. salicifolia stem bark ethyl acetate exhibited antibacterial activity against P. aeruginosa with MIC value of 0.39 mg/mL whereas the methanolic stem and root bark of the same plant inhibited the growth of Proteus mirabilis and Klebsiella pneumoniae with MIC value of 0.781 mg/mL. Conclusion: It was concluded that M. aethiopicum, L. capassa, A. anthelmentica and M. salicifolia are potential source of antibacterial agents. Further studies to establish structures of antibacterial and evaluate active ingredients are recommended.

Keywords: Albizia anthelmentica, Lonchocarpus capassa, Mystroxylon aethiopicum, Myrica salicifolia

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Authors: Qiming Wang

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Dynamic polymer networks (DPNs) crosslinked by dynamic bonds have received intensive attention because of their special crack-healing capability. Diverse DPNs have been synthesized using a number of dynamic bonds, including dynamic covalent bond, hydrogen bond, ionic bond, metal-ligand coordination, hydrophobic interaction, and others. Despite the promising success in the polymer synthesis, the fundamental understanding of their self-healing mechanics is still at the very beginning. Especially, a general analytical model to understand the interfacial self-healing behaviors of DPNs has not been established. Here, we develop polymer-network based analytical theories that can mechanistically model the constitutive behaviors and interfacial self-healing behaviors of DPNs. We consider that the DPN is composed of interpenetrating networks crosslinked by dynamic bonds. bonds obey a force-dependent chemical kinetics. During the self-healing process, we consider the The network chains follow inhomogeneous chain-length distributions and the dynamic polymer chains diffuse across the interface to reform the dynamic bonds, being modeled by a diffusion-reaction theory. The theories can predict the stress-stretch behaviors of original and self-healed DPNs, as well as the healing strength in a function of healing time. We show that the theoretically predicted healing behaviors can consistently match the documented experimental results of DPNs with various dynamic bonds, including dynamic covalent bonds (diarylbibenzofuranone and olefin metathesis), hydrogen bonds, and ionic bonds. We expect our model to be a powerful tool for the self-healing community to invent, design, understand, and optimize self-healing DPNs with various dynamic bonds.

Keywords: self-healing polymers, dynamic covalent bonds, hydrogen bonds, ionic bonds

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Authors: Abdullah Kattan, Khalid Alzahrani, Saud Alsaleh, Loui Ezzat, Khalid Murad, Bader Alghamdi

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Background and Significance: Patients are often bothered by the excess skin laxity and redundancy that they are left with after losing weight. Body-contouring surgery offers a solution to this problem; however, there is scarce literature on the psychological and social effects of these surgeries. This study was conducted to assess the psychosocial impact of body-contouring surgery on patients after weight loss. Methodology: In this cross-sectional study, a specifically designed questionnaire was administered to forty three patients whom have undergone body-contouring surgery. All included patients had lost no less than 20 Kg before body-contouring surgery, and were interviewed at least 6 months after surgery. The twenty-question interviewer based questionnaire was used to assess the psychosocial status of the patients before and after undergoing body-contouring surgery. The questionnaire assessed the quality of life (social life, job performance and sexual activity), presence of symptoms of depression and overall satisfaction. Data was analyzed as paired variables in SPSS using McNemar’s test. Results: Among the 43 participants, 19 (44.2%) have undergone mammoplasty, 12 (27.9%) have undergone abdominoplasty and the remainder of the patients have undergone other various procedures including brachioplasty, thigh lifts and nick liposuction. The mean age of patients was 34 +/- 10, the sample included 24 (55.8%) females and 19 (44.2%) males. The patients’ quality of life significantly improved in the following areas; social life (P<0.001), job performance (P<0.002) and sexual activity (P<0.001). Moreover, 17 (39.5%) patients suffered symptoms of depression before body-contouring surgery; however, only 1 (2.3%) patient suffered symptoms of depression after surgery. Overall satisfaction rate was found to be 62.8%; with mammoplasty being the highest satisfaction rate procedure (66.6 %). Conclusion: Body-contouring surgery after weight loss has shown to improve the psychological and social aspects in patients. These findings have been found to be consistent with the majority of relevant published studies, further increasing reliability of our study.

Keywords: abdominoplasty, body-contouring, mammoplasty, psychosocial

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Authors: Aydin Sipahioglu, Gokhan Celik

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Helicopter routing problem (HRP) is finding good tours for helicopter so as to pick up and deliver personnel or material among specified nodes, mutually. It can be encountered in case of being lots of supply and demand points for different commodities and requiring delivering commodities with helicopter. For instance, to deliver personnel or material from shore to oil rig is a good example. In fact, HRP is a branch of vehicle routing problem with pickup and delivery (VRPPD). However, it has additional constraints such that fuel capacity, performance of helicopter in different altitude and temperature, and the number of maximum takeoff and landing allowed. This kind of pickup and delivery problems can be classified into 3 groups, basically. 1-1 (one to one), M-M (many to many) and 1-M-1 (one to many to one). 1-1 means each commodity has only one supply and one demand point. M-M means there can be more than one supply and demand points for each kind of commodity. 1-M-1 means commodities at depot are delivered to demand points and commodities at customers are delivered to depot. In this case helicopter takes off from its own base, complete its tour and return to its own base. In this study, we define 1-M-M-1 type HRP. That means helicopter takes off from its home base, deliver commodities among the nodes as well as between depot and customers and return to its home base. These problems have NP-hard nature. Therefore, obtaining a good solution in a reasonable time is not easy. In this study, a model is offered for 1-M-M-1 type HRP. It is shown on small scale test instances that the model can find the optimal solution.

Keywords: helicopter routing problem, vehicle routing with pickup and delivery, integer programming

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Authors: Ramin Rostamkhani, Thurasamy Ramayah

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One of the most important topics of today’s industrial organizations is the challenging issue of supply chain management. In this field, scientists and researchers have published numerous practical articles and models, especially in the last decade. In this research, to our best knowledge, the discussion of data modeling of supply chain management components using well-known statistical distribution functions has been considered. The world of science owns mathematics, and showing the behavior of supply chain data based on the characteristics of statistical distribution functions is innovative research that has not been published anywhere until the moment of doing this research. In an analytical process, describing different aspects of functions including probability density, cumulative distribution, reliability, and failure function can reach the suitable statistical distribution function for each of the components of the supply chain management. It can be applied to predict the behavior data of the relevant component in the future. Providing a model to adapt the best statistical distribution function in the supply chain management components will be a big revolution in the field of the behavior of the supply chain management elements in today's industrial organizations. Demonstrating the final results of the proposed model by introducing the process capability indices before and after implementing it alongside verifying the approach through the relevant assessment as an acceptable verification is a final step. The introduced approach can save the required time and cost to achieve the organizational goals. Moreover, it can increase added value in the organization.

Keywords: analyzing, process capability indices, statistical distribution functions, supply chain management components

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Authors: Woosik Jang, Seung H. Han, Seung Won Baek, Chan Young Park

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Natural gas (NG) is a local energy resource that exists in certain countries, and most NG producers operate within unstable governments. Moreover, about 90% of the liquefied natural gas (LNG) market is governed by a small number of international oil companies (IOCs) and national oil companies (NOCs), market entry of second movers is extremely limited. To overcome these barriers, project viability should be assessed based on limited information at the project screening perspective. However, there have been difficulties at the early stages of projects as follows: (1) What factors should be considered? (2) How many experts are needed to make a decision? and (3) How to make an optimal decision with limited information? To answer these questions, this research suggests a LNG project viability assessment model based on the Dempster-Shafer theory (DST). Total of 11 indices for the gas field analysis and 23 indices for the market environment analysis are identified that reflect unique characteristics of LNG industry. Moreover, the proposed model evaluates LNG projects based on questionnaire survey and it provides not only quantified results but also uncertainty level of results based on DST. Consequently, the proposed model as a systematic framework can support the decision-making process from the gas field projects using quantitative results, and it is developed to a stand-alone system to enhance the practical usability. It is expected to improve the decision-making quality and opportunity in LNG projects for enterprise through informed decision.

Keywords: project viability, LNG project, enterprise information system, Dempster-Shafer Theory, strategic decision-making

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Authors: Simon Espigolé, Igor Shalyminov, Helen Hastie

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Deep machine learning techniques including deep neural networks (DNN) have been used to model language and dialogue for conversational agents to perform tasks, such as giving technical support and also for general chit-chat. They have been shown to be capable of generating long, diverse and coherent sentences in end-to-end dialogue systems and natural language generation. However, these systems tend to imitate the training data and will only generate the concepts and language within the scope of what they have been trained on. This work explores how deep neural networks can be used in a task that would normally require human creativity, whereby the human would read the movie description and/or watch the movie and come up with a compelling, interesting movie title. This task differs from simple summarization in that the movie title may not necessarily be derivable from the content or semantics of the movie description. Here, we train a type of DNN called a sequence-to-sequence model (seq2seq) that takes as input a short textual movie description and some information on e.g. genre of the movie. It then learns to output a movie title. The idea is that the DNN will learn certain techniques and approaches that the human movie titler may deploy that may not be immediately obvious to the human-eye. To give an example of a generated movie title, for the movie synopsis: ‘A hitman concludes his legacy with one more job, only to discover he may be the one getting hit.’; the original, true title is ‘The Driver’ and the one generated by the model is ‘The Masquerade’. A human evaluation was conducted where the DNN output was compared to the true human-generated title, as well as a number of baselines, on three 5-point Likert scales: ‘creativity’, ‘naturalness’ and ‘suitability’. Subjects were also asked which of the two systems they preferred. The scores of the DNN model were comparable to the scores of the human-generated movie title, with means m=3.11, m=3.12, respectively. There is room for improvement in these models as they were rated significantly less ‘natural’ and ‘suitable’ when compared to the human title. In addition, the human-generated title was preferred overall 58% of the time when pitted against the DNN model. These results, however, are encouraging given the comparison with a highly-considered, well-crafted human-generated movie title. Movie titles go through a rigorous process of assessment by experts and focus groups, who have watched the movie. This process is in place due to the large amount of money at stake and the importance of creating an effective title that captures the audiences’ attention. Our work shows progress towards automating this process, which in turn may lead to a better understanding of creativity itself.

Keywords: creativity, deep machine learning, natural language generation, movies

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Authors: Mohammadreza Nezamirad, Sepideh Amirahmadian, Nasim Sabetpour, Azadeh Yazdi, Amirmasoud Hamedi

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Cavitation inside diesel injector nozzle is investigated using Reynolds-Stress-Navier Stokes equations. Schnerr-Sauer cavitation model is used for modeling cavitation inside diesel injector nozzle. The carrying fluid utilized in the current study is diesel fuel. The flow is verified at the beginning by comparing with the previous experimental data, and it was found that K-Epsilon turbulent model could lead to a better accuracy comparing to K-Omega turbulent model. Moreover, the mass flow rate obtained numerically is compared with the experimental value, and the discrepancy was found to be less than 5 percent which shows the accuracy of the current results. Finally, a real-size four-hole nozzle is investigated, and the flow inside it is visualized based on velocity profile, discharge coefficient, and cavitation number. It was found that the mesh density could be reduced significantly by utilizing periodic boundary conditions. Velocity contour at the mid nozzle showed that the maximum value of velocity occurs at the end of the needle before entering the orifice area. Last but not least, at the same boundary conditions, when different needle heights were utilized, it was found that as needle height increases with an increase in cavitation number, discharge coefficient increases, while the mentioned increases are more tangible at smaller values of needle heights.

Keywords: cavitation, diesel fuel, CFD, real size nozzle, mass flow rate

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Authors: Peter John, Zainab Ali, Attya Bhatti

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Rheumatoid Arthritis (RA) is a systemic autoimmune inflammatory disease that primarily affects the joints. RA is caused in many cases by the interaction between genes and environmental factors, including tobacco, that primarily involves synovial joints. It typically starts in small peripheral joints, is usually symmetric, and progresses to involve proximal joints if left untreated. The prevalence of rheumatoid arthritis varies substantially around the globe, ranging from 0·25% to 1%.3. Rheumatoid arthritis can affect individuals of any age, with an increased incidence in people older than 40 years. Women are affected two to three times more frequently than men. The present work involved evaluating the toxicity and therapeutic potential of Dodonaea viscosa in a collagen-induced arthritic mouse model. Chemical analysis exhibited that Dodonaea viscosa has high levels of beneficial compounds, including phenols, flavonoids, and other phytochemicals. The Dodonaea viscosa showed significant antioxidant, anti-inflammatory, and anti-arthritic potential without toxic effects. Arthritic mice treated with Dodonaea viscosa showed reduced levels of rheumatoid factor and paw edema, while no significant effects on spleen indices and radiological examination of paws were found compared to control untreated arthritic mice. In summary, the Dodonaea viscosa treatment results in improvement in Arthritic Mice Model for which further studies are required.

Keywords: rheumatoid arthritis, dodonaea viscisa, anti-inflammatory, anti-rheumatic

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Authors: Zhao Pengcheng, Yin Siyuan

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Fintech is the new hot topic of the 21st century, a discipline that combines financial theory with computer modelling. It can provide both digital analysis methods for investment banks and investment decisions for users. Given the variety of services available, it is necessary to provide a superior method of requirements elicitation to ensure that users' needs are addressed in the software development process. The accuracy of traditional software requirements elicitation methods is not sufficient, so this study attempts to use a multi-perspective based requirements heuristic framework. Methods such as interview and questionnaire combination, card sorting, and model driven are proposed. The collection results from PCA show that the new methods can better help with requirements elicitation. However, the method has some limitations and, there are some efficiency issues. However, the research in this paper provides a good theoretical extension that can provide researchers with some new research methods and perspectives viewpoints.

Keywords: requirement elicitation, FinTech, mobile application, survey, interview, model-driven

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Authors: Li̇zan Mahmood Khorsheed Zangana

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Experimental and numerical investigations have been carried out to study the mechanism of separation energy and flow phenomena in the counter-flow vortex tube. This manuscript presents a complete comparison between the experimental investigation and CFD analysis. The experimental model tested under different inlet pressures. Three-dimensional numerical modelling using the k-ε model. The results show any increase in both cold mass fraction and inlet pressure caused to increase ΔTc, and the maximum ΔTc value occurs at P = 6 bar. The coefficient of performance (COP) of two important factors in the vortex tube have been evaluated, which ranged from 0.25 to 0.74. The maximum axial velocity is 93, where it occurs at the tube axis close the inlet exit (Z/L=0.2). The results showed a good agreement for experimental and numerical analysis.

Keywords: counter flow, vortex tube, computational fluid dynamics analysis, energy separation, experimental study

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Authors: Yeon Ho Je

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A novel recombinant baculovirus, NeuroBactrus, was constructed to develop an improved baculovirus insecticide with additional beneficial properties, such as a higher insecticidal activity and improved recovery, compared to wild-type baculovirus. For the construction of NeuroBactrus, the Bacillus thuringiensis crystal protein gene (here termed cry1-5) was introduced into the Autographa californica nucleopolyhedrovirus (AcMNPV) genome by fusion of the polyhedrin–cry1-5–polyhedrin genes under the control of the polyhedrin promoter. In the opposite direction, an insect-specific neurotoxin gene, AaIT, from Androctonus australis was introduced under the control of an early promoter from Cotesia plutellae bracovirus by fusion of a partial fragment of orf603. The polyhedrin–Cry1-5–polyhedrin fusion protein expressed by the NeuroBactrus was not only occluded into the polyhedra, but it was also activated by treatment with trypsin, resulting in an_65-kDa active toxin. In addition, quantitative PCR revealed that the neurotoxin was expressed from the early phase of infection. NeuroBactrus showed a high level of insecticidal activity against Plutella xylostella larvae and a significant reduction in the median lethal time against Spodoptera exigua larvae compared to those of wild-type AcMNPV. Rerecombinant mutants derived from NeuroBactrus in which AaIT and/or cry1-5 were deleted were generated by serial passages in vitro. Expression of the foreign proteins (B. thuringiensis toxin and AaIT) was continuously reduced during the serial passage of the NeuroBactrus. Moreover, polyhedra collected from S. exigua larvae infected with the serially passaged NeuroBactrus showed insecticidal activity similar to that of wild-type AcMNPV. These results suggested that NeuroBactrus could be recovered to wild-type AcMNPV through serial passaging.

Keywords: baculovirus, insecticide, neurotoxin, neurobactrus

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Authors: Matej Buzgo, Erico Himawan, Ksenija JašIna, Aiva Simaite

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Electrospinning is a versatile and efficient technology for producing nanofibers for biomedical applications. One of the most common polymers used for the preparation of nanofibers for regenerative medicine and drug delivery applications is polycaprolactone (PCL). PCL is a biocompatible and bioabsorbable material that can be used to stimulate the regeneration of various tissues. It is also a common material used for the development of drug delivery systems by blending the polymer with small active molecules. However, for many drug delivery applications, e.g. cancer immunotherapy, PCL biodegradation rate that may exceed 9 months is too long, and faster nanofiber dissolution is needed. In this paper, we investigate the dissolution and small molecule release rates of PCL blends with two hydrophilic polymers: polyethylene oxide (PEO) or polyvinylpyrrolidone (PVP). We show that adding hydrophilic polymer to the PCL reduces the water contact angle, increases the dissolution rate, and strengthens the interactions between the hydrophilic drug and polymer matrix that further sustain its release. Finally using this method, we were also able to increase the nanofiber degradation rate when PCL-PEO and PCL-PVP were used as a shell in the electrospun core-shell nanofibers and spread up the release of active proteins from their core. Electrospinning can be used for the preparation of the core-shell nanofibers, where active ingredients are encapsulated in the core and their release rate is regulated by the shell. However, such fibers are usually prepared by coaxial electrospinning that is an extremely low-throughput technique. An alternative is emulsion electrospinning that could be upscaled using needleless blades. In this work, we investigate the possibility of using emulsion electrospinning for encapsulation and sustained release of the growth factors for the development of the organotypic skin models. The core-shell nanofibers were prepared using the optimized formulation and the release rate of proteins from the fibers was investigated for 2 weeks – typical cell culture conditions.

Keywords: electrospinning, polycaprolactone (PCL), polyethylene oxide (PEO), polyvinylpyrrolidone (PVP)

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Authors: Ananchai Ukaew, Choopong Chauypen

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Design concepts of real-time embedded system can be realized initially by introducing novel design approaches. In this literature, model based design approach and in-the-loop testing were employed early in the conceptual and preliminary phase to formulate design requirements and perform quick real-time verification. The design and analysis methodology includes simulation analysis, model based testing, and in-the-loop testing. The design of conceptual drive-by-wire, or DBW, algorithm for electronic control unit, or ECU, was presented to demonstrate the conceptual design process, analysis, and functionality evaluation. The concepts of DBW ECU function can be implemented in the vehicle system to improve electric vehicle, or EV, conversion drivability. However, within a new development process, conceptual ECU functions and parameters are needed to be evaluated. As a result, the testing system was employed to support conceptual DBW ECU functions evaluation. For the current setup, the system components were consisted of actual DBW ECU hardware, electric vehicle models, and control area network or CAN protocol. The vehicle models and CAN bus interface were both implemented as real-time applications where ECU and CAN protocol functionality were verified according to the design requirements. The proposed system could potentially benefit in performing rapid real-time analysis of design parameters for conceptual system or software algorithm development.

Keywords: drive-by-wire ECU, in-the-loop testing, model-based design, real-time embedded system

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

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Authors: Dharshika Rajalingam, Jeffery W. Peng

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Acinetobacter baumannii is a challenging threat to global health, recognized as a multidrug-resistant pathogen. -lactamase is one of the principal resistant mechanisms developed by A. baumannii to survive against -lactam antibiotics. OXA24/40 is one of the types of -lactamases, a well-documented carbapenem hydrolyzing class D -lactamases (CHDL). It was revealed that OXA24/40 showed resistivity against doripenem, one of the carbapenems, by two different mechanisms as hydrolysis and -lactonization. Furthermore, it undergoes genetic mutations to broaden the -lactamase activity to survive against antibiotic environments. One of the crucial characterizations of prokaryotes to develop adaptation is post-translational modification (PTM), mainly phosphorylation. However, the PTM of OXA24/40 is an unknown feature, and the impact of PTM on antibiotic resistivity is yet to be explored. We approached these hypotheses using NMR and MS techniques and found that the OXA24/40 could be phosphorylated in vitro. The Ser81 at the active STFK motif of OXA24/40 of catalytic pocket was identified as the site of phosphorylation using 1D 31P NMR experiment, whereas S81 is required to form an acyl-enzyme complex between enzyme and -lactam antibiotics. The activity of completely phosphorylated OXA24/40 wild type against doripenem revealed that the phosphorylation of active Ser inactivates the -lactamases activity of OXA24/40. The 1D 1H CPMG NMR-based activity assay of phosphorylated OXA24/40 against doripenem confirmed that both deactivating mechanisms are inhibited by phosphorylation. Carbamylated Lysine at the active STFK motif is one of the critical features of CHDL required for the acylation and deacylation reactions of the enzyme. The 1D 13C NMR experiment confirmed that the K84 of phosphorylated OXA24/40 is de-carbamylated. Phosphorylation of OXA24/40 affects both active S81 and carbamylated K84 of OXA24 that are required for the resistivity of -lactamase. So, phosphorylation could be one of the reasons for the genetic mutation of OXA24/40 for the development of antibiotic resistivity. Further research can lead to an understanding of the effect of phosphorylation on the clinical mutants of the OXA24-like -lactamase family on the broadening of -lactamase activity.

Keywords: OXA24/40, phosphorylation, clinical mutants, resistivity

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Authors: Subhash Chandra Sharma, Mohammad Soleimani

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Selection of the correct lubricant for the top of rail application is a complex process. In this paper, the selection of the proper lubricant for a Top-Of-Rail (TOR) lubrication system based on graph theory and matrix approach has been developed. Attributes influencing the selection process and their influence on each other has been represented through a digraph and an equivalent matrix. A matrix function which is called the Permanent Function is derived. By substituting the level of inherent contribution of the influencing parameters and their influence on each other qualitatively, a criterion called Suitability Index is derived. Based on these indices, lubricants can be ranked for their suitability. The proposed model can be useful for maintenance engineers in selecting the best lubricant for a TOR application. The proposed methodology is illustrated step–by-step through an example.

Keywords: lubricant selection, top of rail lubrication, graph-theory, Ranking of lubricants

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Authors: Norshakirah Ab.Aziz, Nurul Atiqah Jamaluddin

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Consequently, electronic word-of-mouth (e-WoM) becomes one of the resources in the decision making process and considered a valuable marketing channel for consumers and organizations. Admittedly, there is increasing concern on the accuracy and genuine of e-WoM content because consumers prefer to look out product or service information available online. Thus, the focus of this study is to propose a model and guidelines how to select trusted online review content according to domain chosen –undergrad students smartphone online review. Undeniable, mobile devices like smartphone has now become a necessity in today are daily life to complete our daily chores. The model and guideline focused on product competency review and the message integrity. In other words, this study aims to enable consumers to identify trusted online review content, which helps them in buying decisions.

Keywords: electronic word of mouth, e-WoM, WoM, online review

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Authors: Sebai Amal, Massuel Sylvain

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Groundwater is the key element of the development of most of the semi-arid areas where water resources are increasingly scarce due to an irregularity of precipitation, on the one hand, and an increasing demand on the other hand. This is the case of the watershed of the Central Tunisia Merguellil, object of the present study, which focuses on an implementation of an underground flows hydrodynamic model to understand the recharge processes of the Kairouan’s plain groundwater by aquifers boundary through the hydraulic threshold of El Haouareb. The construction of a conceptual geological 3D model by the Hydro GeoBuilder software has led to a definition of the aquifers geometry in the studied area thanks to the data acquired by the analysis of geologic sections of drilling and piezometers crossed shells partially or in full. Overall analyses of the piezometric Chronicles of different piezometers located at the level of the dam indicate that the influence of the dam is felt especially in the aquifer carbonate which confirms that the dynamics of this aquifer are highly correlated to the dam’s dynamic. Groundwater maps, high and low-water dam, show a flow that moves towards the threshold of El Haouareb to the discharge of the waters of Ain El Beidha discharge towards the plain of Kairouan. Software FEFLOW 5.2 steady hydrodynamic modeling to simulate the hydraulic threshold at the level of the dam El Haouareb in a satisfactory manner. However, the sensitivity study to the different parameters shows equivalence problems and a fix to calibrate the limestones’ permeability. This work could be improved by refining the timing steady and amending the representation of limestones in the model.

Keywords: Hydrodynamic modeling, lithological modeling, hydraulic, semi-arid, merguellil, central Tunisia

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Authors: Arlett A. Rosado-Torres, Ismael Marino-Tapia

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Changes in benthic cover of coral dominated systems to macroalgae dominance are widely studied worldwide. Watershed pollutants are potentially as important as overfishing causing phase shift. In certain regions of the world most of the continental inputs are through submarine groundwater discharges (SGD), which can play a significant ecological role because the concentration of its nutrients is usually greater that the one found in surface seawater. These stressors have adversely affected coral reefs, particularly in the Caribbean. Measurements of benthic cover (with video tracing, through a Go Pro camera), reef roughness (acoustic estimates with an Acoustic Doppler Current Velocity profiler and a differential GPS), thermohaline conditions (conductivity-temperature-depth (CTD) instrument) and nutrient measurements were taken in different sites in the reef lagoon of Puerto Morelos, Q. Roo, Mexico including those with influence of SGD and without it. The results suggest a link between SGD, macroalgae cover and structural complexity. Punctual water samples and data series from a CTD Diver confirm the presence of the SGD. On the site where the SGD is, the macroalgae cover is larger than in the other sites. To establish a causal link between this phase shift and SGD, the DELFT 3D hydrodynamic model (FLOW and WAVE modules) was performed under different environmental conditions and discharge magnitudes. The model was validated using measurements of oceanographic instruments anchored in the lagoon and forereef. The SGD is consistently favoring macroalgae populations and affecting structural complexity of the reef.

Keywords: hydrodynamic model, macroalgae, nutrients, phase shift

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Authors: Jongho Park, Jinwoong Choi, Sungnam Hong, Seung-Kyung Kye, Sun-Kyu Park

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Recently, to cope with the rapidly changing construction trend because of aging infrastructures, modular bridge technology has been studied actively. Modular bridge is easily constructed by assembling standardized precast structure members in the field. It will be possible to construct rapidly and reduce construction cost efficiently. However, the shape examination of the transverse connection of T-type girder newly developed between the segmented modules is not performed. Therefore, the investigation of the connection shape is needed. In this study, shape of the modular T-girder bridge transverse connection was analyzed by finite element model that was verified in study which was verification of model for transverse connection using Abaqus. Connection angle was chosen as the parameter. The result of analyses showed that optimal value of angle is 130 degree.

Keywords: modular bridge, optimal transverse shape, parameter, FEM

Procedia PDF Downloads 638

Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

Abstract:

Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

Procedia PDF Downloads 127

Authors: James Killian, Sarah Cox

Abstract:

The use of stability criteria within geotechnical engineering is the way the results of analyses are conveyed, and sensitivities and risk assessments are performed. Historically, the primary stability criteria for slope design has been the Factor of Safety (FOS) coming from a limit calculation. Increasingly, the value derived from Strength Reduction Factor (SRF) analysis is being used as the criteria for stability analysis. The purpose of this work was to study in detail the relationship between SRF values produced from a numerical modeling technique and the traditional FOS values produced from Limit Equilibrium (LEM) analyses. This study utilized a model of a 3000-foot-high slope with a 45-degree slope angle, assuming a perfectly plastic mohr-coulomb constitutive model with high cohesion and friction angle values typical of a large hard rock mine slope. A number of variables affecting the values of the SRF in a numerical analysis were tested, including zone size, in-situ stress, tensile strength, and dilation angle. This paper demonstrates that in most cases, SRF values are lower than the corresponding LEM FOS values. Modeled zone size has the greatest effect on the estimated SRF value, which can vary as much as 15% to the downside compared to FOS. For consistency when using SRF as a stability criteria, the authors suggest that numerical model zone sizes should not be constructed to be smaller than about 1% of the overall problem slope height and shouldn’t be greater than 2%. Future work could include investigations of the effect of anisotropic strength assumptions or advanced constitutive models.

Keywords: FOS, SRF, LEM, comparison

Procedia PDF Downloads 283

Authors: Davut Disci

Abstract:

Objective: to measure the factors affecting expectations and intentions of using mobile phone in educational contexts by university students, using advanced equations and modeling techniques. Design and Methodology: According to the literature, Mobile Addiction, Parental Surveillance- Safety/Security, Social Relations, and Mobile Behavior are most used terms of defining mobile use of people. Therefore these variables are tried to be measured to find and estimate their effects on expectations and intentions of using mobile phone in educational context. 421 university students participated in this study and there are 229 Female and 192 Male students. For the purpose of examining the mobile behavior and educational expectations and intentions, a questionnaire is prepared and applied to the participants who had to answer all the questions online. Furthermore, responses to close-ended questions are analyzed by using The Statistical Package for Social Sciences(SPSS) software, reliabilities are measured by Cronbach’s Alpha analysis and hypothesis are examined via using Multiple Regression and Linear Regression analysis and the model is tested with Structural Equation Modeling(SEM) technique which is important for testing the model scientifically. Besides these responses, open-ended questions are taken into consideration. Results: When analyzing data gathered from close-ended questions, it is found that Mobile Addiction, Parental Surveillance, Social Relations and Frequency of Using Mobile Phone Applications are affecting the mobile behavior of the participants in different levels, helping them to use mobile phone in educational context. Moreover, as for open-ended questions, participants stated that they use many mobile applications in their learning environment in terms of contacting with friends, watching educational videos, finding course material via internet. They also agree in that mobile phone brings greater flexibility to their lives. According to the SEM results the model is not evaluated and it can be said that it may be improved to show in SEM besides in multiple regression. Conclusion: This study shows that the specified model can be used by educationalist, school authorities to improve their learning environment.

Keywords: education, mobile behavior, mobile learning, technology, Turkey

Procedia PDF Downloads 410

Authors: Mohamed Mohamed, Philip Bonello, Peter Russhard

Abstract:

Blade Tip Timing (BTT) is a technology concerned with the estimation of both frequency and amplitude of rotating blades. A BTT system comprises two main parts: (a) the arrival time measurement system, and (b) the analysis algorithms. Simulators play an important role in the development of the analysis algorithms since they generate blade tip displacement data from the simulated blade vibration under controlled conditions. This enables an assessment of the performance of the different algorithms with respect to their ability to accurately reproduce the original simulated vibration. Such an assessment is usually not possible with real engine data since there is no practical alternative to BTT for blade vibration measurement. Most simulators used in the literature are based on a simple spring-mass-damper model to determine the vibration. In this work, a more realistic experimentally validated simulator based on the Finite Element (FE) model of a bladed disc (blisk) is first presented. It is then used to generate the necessary data for the assessment of different BTT algorithms. The FE modelling is validated using both a hammer test and two firewire cameras for the mode shapes. A number of autoregressive methods, fitting methods and state-of-the-art inverse methods (i.e. Russhard) are compared. All methods are compared with respect to both synchronous and asynchronous excitations with both single and simultaneous frequencies. The study assesses the applicability of each method for different conditions of vibration, amount of sampling data, and testing facilities, according to its performance and efficiency under these conditions.

Keywords: blade tip timing, blisk, finite element, vibration measurement

Procedia PDF Downloads 296

Authors: Shishay Kidanu, Abdullah Alhaj

Abstract:

Sinkholes in the karst terrain of Greene County, Missouri, pose significant geohazards, imposing challenges on construction and infrastructure development, with potential threats to lives and property. To address these issues, understanding the influencing factors and modeling sinkhole susceptibility is crucial for effective mitigation through strategic changes in land use planning and practices. This study utilizes geographic information system (GIS) software to collect and process diverse data, including topographic, geologic, hydrogeologic, and anthropogenic information. Nine key sinkhole influencing factors, ranging from slope characteristics to proximity to geological structures, were carefully analyzed. The Frequency Ratio method establishes relationships between attribute classes of these factors and sinkhole events, deriving class weights to indicate their relative importance. Weighted integration of these factors is accomplished using the Analytic Hierarchy Process (AHP) and the Weighted Linear Combination (WLC) method in a GIS environment, resulting in a comprehensive sinkhole susceptibility index (SSI) model for the study area. Employing Jenk's natural break classifier method, the SSI values are categorized into five distinct sinkhole susceptibility zones: very low, low, moderate, high, and very high. Validation of the model, conducted through the Area Under Curve (AUC) and Sinkhole Density Index (SDI) methods, demonstrates a robust correlation with sinkhole inventory data. The prediction rate curve yields an AUC value of 74%, indicating a 74% validation accuracy. The SDI result further supports the success of the sinkhole susceptibility model. This model offers reliable predictions for the future distribution of sinkholes, providing valuable insights for planners and engineers in the formulation of development plans and land-use strategies. Its application extends to enhancing preparedness and minimizing the impact of sinkhole-related geohazards on both infrastructure and the community.

Keywords: sinkhole, GIS, analytical hierarchy process, frequency ratio, susceptibility, Missouri

Procedia PDF Downloads 62

Authors: Lee Woong-Kyu

Abstract:

Fierce competition in smartphone market may encourage users to switch brands when buying a new smartphone. However, many smartphone users continue to use the same brand although other branded smartphones are perceived to be more attractive. The purpose of this study is to identify and analyze the effects of brand loyalty toward incumbent smartphone on new smartphone adoption. For this purpose, a research model including two hypotheses, the positive effect on rational judgments and the negative effect on rational judgments, are proposed based on the dual process theory. For the validation of the research model, the data was collected by surveying Korean university students and tested by the group comparison between high and low brand loyalty. The results show that the two hypotheses were statistically supported.

Keywords: brand loyalty, dual process theory, incumbent smartphone, smartphone adoption

Procedia PDF Downloads 280

Authors: Davut Disci

Abstract:

Objective: to measure the factors affecting expectations and intentions of using mobile phone in educational contexts by university students, using advanced equations and modeling techniques. Design and Methodology: According to the literature, Mobile Addiction, Parental Surveillance-Safety/Security, Social Relations, and Mobile Behavior are most used terms of defining mobile use of people. Therefore, these variables are tried to be measured to find and estimate their effects on expectations and intentions of using mobile phone in educational context. 421 university students participated in this study and there are 229 Female and 192 Male students. For the purpose of examining the mobile behavior and educational expectations and intentions, a questionnaire is prepared and applied to the participants who had to answer all the questions online. Furthermore, responses to close-ended questions are analyzed by using The Statistical Package for Social Sciences(SPSS) software, reliabilities are measured by Cronbach’s Alpha analysis and hypothesis are examined via using Multiple Regression and Linear Regression analysis and the model is tested with Structural Equation Modeling (SEM) technique which is important for testing the model scientifically. Besides these responses, open-ended questions are taken into consideration. Results: When analyzing data gathered from close-ended questions, it is found that Mobile Addiction, Parental Surveillance, Social Relations and Frequency of Using Mobile Phone Applications are affecting the mobile behavior of the participants in different levels, helping them to use mobile phone in educational context. Moreover, as for open-ended questions, participants stated that they use many mobile applications in their learning environment in terms of contacting with friends, watching educational videos, finding course material via internet. They also agree in that mobile phone brings greater flexibility to their lives. According to the SEM results the model is not evaluated and it can be said that it may be improved to show in SEM besides in multiple regression. Conclusion: This study shows that the specified model can be used by educationalist, school authorities to improve their learning environment.

Keywords: learning technology, instructional technology, mobile learning, technology

Procedia PDF Downloads 442