Search results for: soil-post interaction modeling

Authors: Janneke K. Oostrom, Richard Ronay

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The so called “red sneakers effect” refers to people’s inclination to infer status and competence from signals of nonconformity. In the current research, we explore an untested possible boundary condition to the red sneakers effect within the context of personnel selection. In two experimental studies (total N = 156), we examined how (non)conforming dress style interacts with the quality of a job applicant’s resume to determine hirability perceptions. We found that dress style indeed impacts hirability perceptions, but that the exact impact depends on the quality of the applicant’s resume. Results revealed that applicants with a low quality resume were punished for behaving in a nonconforming way, whereas applicants with a high quality resume appeared to have the leeway to dress as they please. Importantly, the observed interaction effect was mediated by perceptions of power. These findings suggest that nonconforming dress acts as a power-signaling mechanism in the context of personnel selection. However, the signaling effects of non-conforming dress style can backfire when accompanied by evidence that such posturing is not matched by cues of actual competence.

Keywords: clothing, hirability, nonconformity, personnel selection, power

Procedia PDF Downloads 163

Authors: Rajwanlop Kumpoopong, Sukit Yindeesuk, Pornchai Silarom

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Modeling cracks in concrete is complicated by its strain-softening behavior which requires the use of sophisticated energy criteria of fracture mechanics to assure stable and convergent solutions in the finite-element (FE) analysis particularly for relatively large structures. However, for small-scale structures such as beams and slabs, a simpler approach relies on retaining some shear stiffness in the cracking plane has been adopted in literature to model the strain-softening behavior of concrete under monotonically increased loading. According to the shear retaining approach, each element is assumed to be an isotropic material prior to cracking of concrete. Once an element is cracked, the isotropic element is replaced with an orthotropic element in which the new orthotropic stiffness matrix is formulated with respect to the crack orientation. The shear transfer factor of 0.5 is used in parallel to the crack plane. The shear retaining approach is adopted in this research to model cracks in RC bridge deck with some modifications to take into account the effect of repetitive moving truck wheel loads as they cause fatigue cracking of concrete. First modification is the introduction of fatigue tests of concrete and reinforcing steel and the Palmgren-Miner linear criterion of cumulative damage in the conventional FE analysis. For a certain loading, the number of cycles to failure of each concrete or RC element can be calculated from the fatigue or S-N curves of concrete and reinforcing steel. The elements with the minimum number of cycles to failure are the failed elements. For the elements that do not fail, the damage is accumulated according to Palmgren-Miner linear criterion of cumulative damage. The stiffness of the failed element is modified and the procedure is repeated until the deck slab fails. The total number of load cycles to failure of the deck slab can then be obtained from which the S-N curve of the deck slab can be simulated. Second modification is the modification in shear transfer factor. Moving loading causes continuous rubbing of crack interfaces which greatly reduces shear transfer mechanism. It is therefore conservatively assumed in this study that the analysis is conducted with shear transfer factor of zero for the case of moving loading. A customized FE program has been developed using the MATLAB software to accomodate such modifications. The developed procedure has been validated with the fatigue test of the 1/6.6-scale AASHTO bridge deck under the applications of both fixed-point repetitive loading and moving loading presented in the literature. Results are in good agreement both experimental vs. simulated S-N curves and observed vs. simulated crack patterns. Significant contribution of the developed procedure is a series of S-N relations which can now be simulated at any desired levels of cracking in addition to the experimentally derived S-N relation at the failure of the deck slab. This permits the systematic investigation of crack propagation or deterioration of RC bridge deck which is appeared to be useful information for highway agencies to prolong the life of their bridge decks.

Keywords: bridge deck, cracking, deterioration, fatigue, finite-element, moving truck, reinforced concrete

Procedia PDF Downloads 233

Authors: Seyed Amin Vakili, Sahar Sadat Vakili, Seyed Ehsan Vakili, Nader Abdoli Yazdi

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The purpose of this article is to analyze the finite displacement of Columns by applying the Modified Newmark Method. This research will be performed on Columns subjected to compressive axial load, therefore the non-linearity of the geometry is also considered. If the considered strut is perfect, the governing differential equation contains a branching point in the solution path. Investigation into the Elastica is a part of generalizing the developed method. It presents the ability of the Modified Newmark Method in treating non-linear differential equations Derived from elastic strut stability problems. These include not only an approximate polynomial solution for the Elastica problems, but can also recognize the branching point and the stable solution. However, this investigation deals with the post-buckling response of elastic and pin ended columns subjected to central or equally eccentric axial loads.

Keywords: columns, structural modeling, structures & structural stability, loads

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Authors: S. R. Nikhashemi, Laily Haj Paim, Ali Khatibi

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Structural Equation Modeling (SEM) was used to test a hypothesized model explaining Malaysian hypermarket customers’ perceptions of brand trust (BT), customer perceived value (CPV) and perceived service quality (PSQ) on building their brand loyalty (CBL) and generating positive word-of-mouth communication (WOM). Self-administered questionnaires were used to collect data from 374 Malaysian hypermarket customers from Mydin, Tesco, Aeon Big and Giant in Kuala Lumpur, a metropolitan city of Malaysia. The data strongly supported the model exhibiting that BT, CPV and PSQ are prerequisite factors in building customer brand loyalty, while PSQ has the strongest effect on prediction of customer brand loyalty compared to other factors. Besides, the present study suggests the effect of the aforementioned factors via customer brand loyalty strongly contributes to generate positive word of mouth communication.

Keywords: brand trust, perceived value, Perceived Service Quality, Brand loyalty, positive word of mouth communication

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Authors: M. Ndeley

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The performance of global manufacturing supply chains depends on the interaction of production and transport processes. Currently, the scheduling of these processes is done separately without considering mutual requirements, which leads to no optimal solutions. An integrated scheduling of both processes enables the improvement of supply chain performance. The integrated production and transport scheduling problem (PTSP) is NP-hard, so that heuristic methods are necessary to efficiently solve large problem instances as in the case of global manufacturing supply chains. This paper presents a heuristic scheduling approach which handles the integration of flexible production processes with intermodal transport, incorporating flexible land transport. The method is based on a graph that allows a reformulation of the PTSP as a shortest path problem for each job, which can be solved in polynomial time. The proposed method is applied to a supply chain scenario with a manufacturing facility in South Africa and shipments of finished product to customers within the Country. The obtained results show that the approach is suitable for the scheduling of large-scale problems and can be flexibly adapted to different scenarios.

Keywords: production and transport scheduling problem, graph based scheduling, integrated scheduling

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Authors: Mohamed Khallaf, Hossein M Rizeei

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Simulating wind pattern behavior over proposed urban features is critical in the early stage of the conceptual design of both architectural and urban disciplines. However, it is typically not possible for designers to explore the impact of wind flow profiles across new urban developments due to a lack of real data and inaccurate estimation of building parameters. Modeling the details of existing and proposed urban features and testing them against wind flows is the missing part of the conceptual design puzzle where architectural and urban discipline can focus. This research aims to develop a spatial decision-support design method utilizing LiDAR, GIS, and performance-based wind simulation technology to mitigate wind-related hazards on a design by simulating alternative design scenarios at the pedestrian level prior to its implementation in Sydney, Australia. The result of the experiment demonstrates the capability of the proposed framework to improve pedestrian comfort in relation to wind profile.

Keywords: spatial decision-support design, performance-based wind simulation, LiDAR, GIS

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Authors: Rizka Ardhiyana, Liesbetini Haditjaroko, Sri Mulijani, Reki Ashadi Wicaksono, Raafqi Ranasasmita

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Designing a sensitive, specific and easy to use method to detect pork contamination in the food industry remains a major challenge. In the current study, we developed a sensitive thiol-bond AuNP-Probe biosensor that will change color when detecting pork DNA in the Cytochrome B region. The interaction between the biosensors and DNA sample is measured by spectrophotometer at 540 nm. The biosensor is made by reducing gold with trisodium citrate to produce gold nanoparticle with 39.05 nm diameter. The AuNP-Probe biosensor (gold nanoprobe) achieved 16.04 ng DNA/µl limit of detection and 53.48 ng DNA/µl limit of quantification. The linearity (R2) between color absorbance changes and DNA concentration is 0.9916. The biosensor has a good specificty as it does not cross-react with DNA of chicken and beef. To verify specificity towards the target sequence, PCR was tested to the target sequence and reacted to the PCR product with the biosensor. The PCR DNA isolate resulted in a 2.7 fold higher absorbance compared to pork-DNA isolate alone (without PCR). The sensitivity and specificity of the method show the promising application of the thiol-bond AuNP biosensor in pork-detection.

Keywords: biosensor, DNA probe, gold nanoparticle (AuNP), pork meat, qPCR

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Authors: M. Pomianek, M. Piszczek, M. Maciejewski

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The binocular eye tracking technology is increasingly being used in industry, entertainment and marketing analysis. In the case of virtual reality, eye tracking systems are already the basis for user interaction with the environment. In such systems, the high accuracy of determining the user's eye fixation point is very important due to the specificity of the virtual reality head-mounted display (HMD). Often, however, there are unknown errors occurring in the used eye tracking technology, as well as those resulting from the positioning of the devices in relation to the user's eyes. However, can the virtual environment itself influence estimation errors? The paper presents mathematical analyses and empirical studies of the determination of the fixation point and errors resulting from the change in the size of the pupil in response to the intensity of the displayed scene. The article contains both static laboratory tests as well as on the real user. Based on the research results, optimization solutions were proposed that would reduce the errors of gaze estimation errors. Studies show that errors in estimating the fixation point of vision can be minimized both by improving the pupil positioning algorithm in the video image and by using more precise methods to calibrate the eye tracking system in three-dimensional space.

Keywords: eye tracking, fixation point, pupil size, virtual reality

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Authors: Marina Passero, Tianhua Zhai, Zuyi (Jacky) Huang

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Alzheimer’s disease has become a major public health issue, as indicated by the increasing populations of Americans living with Alzheimer’s disease. After decades of extensive research in Alzheimer’s disease, only seven drugs have been approved by Food and Drug Administration (FDA) to treat Alzheimer’s disease. Five of these drugs were designed to treat the dementia symptoms, and only two drugs (i.e., Aducanumab and Lecanemab) target the progression of Alzheimer’s disease, especially the accumulation of amyloid-b plaques. However, controversial comments were raised for the accelerated approvals of either Aducanumab or Lecanemab, especially with concerns on safety and side effects of these two drugs. There is still an urgent need for further drug discovery to target the biological processes involved in the progression of Alzheimer’s disease. Excessive cholesterol has been found to accumulate in the brain of those with Alzheimer’s disease. Cholesterol can be synthesized in both the blood and the brain, but the majority of biosynthesis in the adult brain takes place in astrocytes and is then transported to the neurons via ApoE. The blood brain barrier separates cholesterol metabolism in the brain from the rest of the body. Various proteins contribute to the metabolism of cholesterol in the brain, which offer potential targets for Alzheimer’s treatment. In the astrocytes, SREBP cleavage-activating protein (SCAP) binds to Sterol Regulatory Element-binding Protein 2 (SREBP2) in order to transport the complex from the endoplasmic reticulum to the Golgi apparatus. Cholesterol is secreted out of the astrocytes by ATP-Binding Cassette A1 (ABCA1) transporter. Lipoprotein receptors such as triggering receptor expressed on myeloid cells 2 (TREM2) internalize cholesterol into the microglia, while lipoprotein receptors such as Low-density lipoprotein receptor-related protein 1 (LRP1) internalize cholesterol into the neuron. Cytochrome P450 Family 46 Subfamily A Member 1 (CYP46A1) converts excess cholesterol to 24S-hydroxycholesterol (24S-OHC). Cholesterol has been approved for its direct effect on the production of amyloid-beta and tau proteins. The addition of cholesterol to the brain promotes the activity of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1), secretase, and amyloid precursor protein (APP), which all aid in amyloid-beta production. The reduction of cholesterol esters in the brain have been found to reduce phosphorylated tau levels in mice. In this work, a computational pipeline was developed to identify the protein targets involved in cholesterol regulation in brain and further to identify chemical compounds as the inhibitors of a selected protein target. Since extensive evidence shows the strong correlation between brain cholesterol regulation and Alzheimer’s disease, a detailed literature review on genes or pathways related to the brain cholesterol synthesis and regulation was first conducted in this work. An interaction network was then built for those genes so that the top gene targets were identified. The involvement of these genes in Alzheimer’s disease progression was discussed, which was followed by the investigation of existing clinical trials for those targets. A ligand-protein docking program was finally developed to screen 1.5 million chemical compounds for the selected protein target. A machine learning program was developed to evaluate and predict the binding interaction between chemical compounds and the protein target. The results from this work pave the way for further drug discovery to regulate brain cholesterol to combat Alzheimer’s disease.

Keywords: Alzheimer’s disease, drug discovery, ligand-protein docking, gene-network analysis, cholesterol regulation

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Authors: Neziha Jaouedi, Noureddine Boujnah, Mohamed Salim Bouhlel

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In the framework of human machine interaction systems enhancement, we focus throw this paper on human behavior analysis and action recognition. Human behavior is characterized by actions and reactions duality (movements, psychological modification, verbal and emotional expression). It’s worth noting that many information is hidden behind gesture, sudden motion points trajectories and speeds, many research works reconstructed an information retrieval issues. In our work we will focus on motion extraction, tracking and action recognition using wavelet network approaches. Our contribution uses an analysis of human subtraction by Gaussian Mixture Model (GMM) and body movement through trajectory models of motion constructed from kalman filter. These models allow to remove the noise using the extraction of the main motion features and constitute a stable base to identify the evolutions of human activity. Each modality is used to recognize a human action using wavelets of derived beta distributions approach. The proposed approach has been validated successfully on a subset of KTH and UCF sports database.

Keywords: feautures extraction, human action classifier, wavelet neural network, beta wavelet

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Authors: Mohammad Moonesun, Ehsan Asadi Asrami, Julia Bodnarchuk

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In the case of Solar Autonomous Underwater Vehicle, which uses photovoltaic panels to provide its required power, due to limitation of energy, accurate estimation of resistance and energy has major sensitivity. In this work, hydrodynamic calculations by numerical method for a solar autonomous underwater vehicle equipped by two 50 W photovoltaic panels has been studied. To evaluate the required power and energy, hull hydrodynamic resistance in several velocities should be taken into account. To do this assessment, the ANSYS FLUENT 18 applied as Computational Fluid Dynamics (CFD) tool that solves Reynolds Average Navier Stokes (RANS) equations around AUV hull, and K-ω SST is used as turbulence model. To validate of solution method and modeling approach, the model of Myring submarine that it’s experimental data was available, is simulated. There is good agreement between numerical and experimental results. Also, these results showed that the K-ω SST Turbulence model is an ideal method to simulate the AUV motion in low velocities.

Keywords: underwater vehicle, hydrodynamic resistance, numerical modelling, CFD, RANS

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Authors: Tomas Linas Šepetys

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In online content-sharing service platforms, the ability of creators to restrict illicit use of audiovisual creative works has effectively been abolished, largely due to specific infrastructure where a huge volume of copyrighted audiovisual content can be made available to the public. The European Union legislator has attempted to strengthen the positions of creators in the realm of online content-sharing services. Article 17 of the new Digital Single Market Directive considers online content-sharing service providers to carry out acts of communication to the public of any creative content uploaded to their platforms by users and posits requirements to obtain licensing agreements. While such regulation intends to assert authors‘ ability to effectively control the dissemination of their creative works, it also creates threats of parody content overblocking through automated content monitoring. Such potentially paradoxical outcome of the efforts of the EU legislator to deliver economic safeguards for the creators in the online content-sharing service platforms leads to presume lack of informity on legislator‘s part regarding creative works‘ economic exploitation opportunities provided to creators in the online content-sharing infrastructure. Analysis conducted in this scientific research discloses that the aforementioned irregularities of parody and other creative content dissemination are caused by EU legislators‘ lack of assessment of value extraction conditions for parody creators in the online content-sharing service platforms. Historical and modeling research method application reveals the existence of two creative content dissemination models and their unique mechanisms of commercial value creation. Obligations to obtain licenses and liability over creative content uploaded to their platforms by users set in Article 17 of the Digital Single Market Directive represent technological replication of the proprietary dissemination model where the creator is able to restrict access to creative content apart from licensed retail channels. The online content-sharing service platforms represent an open dissemination model where the economic potential of creative content is based on the infrastructure of unrestricted access by users and partnership with advertising services offered by the platform. Balanced modeling of proprietary dissemination models in such infrastructure requires not only automated content monitoring measures but also additional regulatory monitoring solutions to separate parody and other types of creative content. An example of the Digital Single Market Directive proves that regulation can dictate not only the technological establishment of a proprietary dissemination model but also a partial reduction of the open dissemination model and cause a disbalance between the economic interests of creators relying on such models. The results of this scientific research conclude an informative role of the creative works dissemination model in the EU copyright law modernization process. A thorough understanding of the commercial prospects of the open dissemination model intrinsic to the online content-sharing service platform structure requires and encourages EU legislators to regulate safeguards for parody content dissemination. Implementing such safeguards would result in a common application of proprietary and open dissemination models in the online content-sharing service platforms and balanced protection of creators‘ economic interests explicitly based on those creative content dissemination models.

Keywords: copyright law, creative works dissemination model, digital single market directive, online content-sharing services

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Authors: Saeb Ahmadi, Mohsen Vafaie Sefti, Mohammad Mahdi Shadman, Ebrahim Tangestani

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Carbon nanotube has shown great potential for the removal of various inorganic and organic components due to properties such as large surface area and high adsorption capacity. Central composite design is widely used method for determining optimal conditions. Also due to the economic reasons and wide application, the rare earth elements are important components. The analyses of cerium (Ce(III)) adsorption as one of the Rare Earth Elements (REEs) adsorption on Multiwall Carbon Nanotubes (MWCNTs) have been studied. The optimization process was performed using Response Surface Methodology (RSM). The optimum amount conditions were pH of 4.5, initial Ce (III) concentration of 90 mg/l and MWCNTs dosage of 80 mg. Under this condition, the optimum adsorption percentage of Ce (III) was obtained about 96%. Next, at the obtained optimum conditions the kinetic and isotherm studied and result showed the pseudo-second order and Langmuir isotherm are more fitted with experimental data than other models.

Keywords: cerium, rare earth element, MWCNTs, adsorption, optimization

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Authors: Elham Rezaee, Sayyed Abbas Tabatabai

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Dual inhibition of COX-2 and sEH enzymes represents one of the distinct pharmaceutical approaches for the treatment of inflammation, pain, cancers, and other diseases. The discovery of these inhibitors for treatment is a great deal of attention because of some advantages such as increased efficacy, a promising safety profile, ease of formulation, and better target engagement. In this research, based on the structure-activity relationship of COX-2 and sEH inhibitors, some amide derivatives with oxadiazole and dihydropyrimidinone rings against sEH and COX-2 enzymes were developed. The designed compounds showed high affinity to the active site of both enzymes in docking studies and were synthesized in good yield and characterized by IR, Mass, 1HNMR, and 13CNMR. All of the novel compounds exhibited considerable in-vitro sEH and COX-2 inhibitory activities in comparison with 12-(3-Adamantan-1-yl-ureido)- dodecanoic acid and celecoxib (a potent urea-based sEH inhibitor and selective nonsteroidal anti-inflammatory drug, respectively). Ethyl 6-methyl-4-(4-(4-(methylsulfonyl)benzamido)phenyl)-2-oxo-1,2,3,4-tetrahydropyrimidine-5-carboxylate was found to be the most selective COX-2 inhibitor (COX-2/COX-1 ratio: 683) with IC50 value of 2.1 nM targeting sEH enzyme.

Keywords: COX-2, dual inhibitors, sEH, synthesis

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Fatemeh Keivanifard

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E-learning is becoming increasingly prominent in higher education, with universities increasing provision and more students signing up. This paper examines factors that predict students' attitudes to adapt e-learning at the Khuzestan province Iran. Understanding the nature of these factors may assist these universities in promoting the use of information and communication technology in teaching and learning. The main focus of the paper is on the university students, whose decision supports effective implementation of e-learning. Data was collected through a survey of 300 post graduate students at the University of dezful, shooshtar and chamran in Khuzestan. The technology adoption model put forward by Davis is utilized in this study. Two more independent variables are added to the original model, namely, the pressure to act and resources availability. The results show that there are five factors that can be used in modeling students' attitudes to adapt e-learning. These factors are intention toward e-learning, perceived usefulness of e-learning, perceived ease of e-learning use, pressure to use e-learning, and the availability of resources needed to use e-learning.

Keywords: e-learning, intention, ease of use, pressure to use, usefulness

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Authors: Neha Bhushan

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For the purpose of this study a village of district Azamgarh has been selected which is a part of the most populous and backward state of the country, Uttar Pradesh. In the age of information, everyone has the right to acquire information and it becomes important to assess the acceptance and non-acceptance of social media among rural population. Rural women of the state are showing positive trends in the form of increased social media and mobile usage. This study is an effort to know the purpose of rural women for using social media. The study design is exploratory and qualitative in nature. Data collection primarily consisted of 25 semi-structured individual interviews having 10 open-ended specific questions in one of the villages of Azamgarh district of Eastern Uttar Pradesh. Sampling approach is flexible and situational. Data reveals that rural women have become active on social media since last six months to one year. Most of them are using Facebook, Whatsapp, and YouTube for the purpose of interaction, learning new skills, checking out recipes and latest fashion. This pilot study gives a bird eye view of the problem and opens door for exploring this least explored area.

Keywords: exploratory research, mobile usage, rural women, social media

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Authors: Ying Yu, Wen-Chi Kuo, Tung-Jung Sung

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The Product-Service System (PSS) has received widespread attention due to the increasing global competition in manufacturing and service markets. Today’s smart products and services are driven by Internet of things (IoT) technologies which will promote the transformation from traditional PSS to smart PSS. Although the smart PSS has some of technological achievements in businesses, it often ignores the real demands of target users when using products and services. Therefore, designers should know and learn the User Experience (UX) of smart products, services and systems. However, both of academia and industry still lack relevant development experience of smart PSS since it is an emerging field. In doing so, this is a case study of Xiaomi’s Chunmi, the largest IoT platform in the world, and addresses the two major issues: (1) why Chunmi should develop smart PSS strategies with UX; and (2) how Chunmi could successfully implement the strategic objectives of smart PSS through the design. The case study results indicated that: (1) the smart PSS can distinguish competitors by their unique UX which is difficult to duplicate; (2) early user engagement is crucial for the success of smart PSS; and (3) interaction, expectation, and enjoyment can be treated as a three-dimensional evaluation of UX design for smart PSS innovation. In conclusion, the smart PSS can gain competitive advantages through good UX design in the market.

Keywords: design, smart PSS, user experience, user engagement

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Authors: Hee-Jung Seo, Yunjung Lee, Areum Han, Heeyoung Park, Se-Hyuk Park

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The purpose of this study was to analyze the relationship between happiness and depression among people with disabilities and to analyze the social phenomenon of leisure activities among them to promote physical and leisure activities for people with disabilities. The research methods included analyzing differences in happiness according to depression classification. A total of 281 people with disabilities were analyzed using SPSS WIN Ver. 29.0. In addition, the SumTrend platform was used to analyze terms related to 'leisure activities for the disabled.' The findings can be summarized into two main points: First, there were significant differences in happiness according to depression classification. Second, there were 20 mentions before COVID-19, 34 mentions after COVID-19, and currently 43 mentions, with high positive rates observed in each period. Based on these results, the following conclusions were drawn: First, measures for people with disabilities include strengthening online resources and services, social distancing response policies, improving accessibility, and providing support and financial assistance. Second, measures for non-disabled individuals emphasize the need for education and information provision, promoting dialogue and interaction, ensuring accessibility, and promoting inclusive cultural awareness and attitude change.

Keywords: leisure activities, individuals with disabilities, COVID-19 pandemic, depression

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Authors: Sukhbir Singh

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This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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Authors: Mohammed Ali Hadj Ammar, Fethi Bouras, Kamel Sahlaoui

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This article presents a detailed study of two working pairs intended for use in solar adsorption refrigeration (SAR) system. The study was based on two indicators: the daily production and coefficient of performance (COP). The thermodynamic cycle of the system is based on the adsorption phenomena at a constant temperature. A computer simulation program has been developed for modeling and performance evaluation for the solar-powered adsorption refrigeration cycle. It was found that maximal cycled mass is obtained by S40/water (0.280kg/kg) followed by CarboTech C40/1/methanol (0.260kg/kg). At a condenser temperature of 30°C, with an adsorbent mass of 38.59 kg, and an integrated collector/bed configuration, the couple CarboTech C40/1/methanol for the ice-maker purpose can reach cycle COP of 0.63 and can produce about 13.6kg ice per day, while the couple S40/water for the air-conditioning can reach cycle COP of 0.66 and 212kg as daily cold-water production. Additionally, adequate indicators are evaluated addressing the economic and environmental associated with each working pair.

Keywords: solar adsorption, refrigeration, activated carbon, silica gel

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Authors: Fatma Zehra Engin Sagirli, Eyup Sabri Kayali, A. Sezai Sarac

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In this study, Poly (acrylonitrile-co-methylacrylate)/N-Methyl Pyrrole and Pyrrole ([P(AN-co-MA)]-NMPy and [P(AN-co-MA)]-PPy) core–shell nanoparticles were obtained by in situ emulsion polymerization in the presence of Sodium dodecyl benzene sulfonate and sodium dodecyl sulfate (SDBS and SDS) by using ammonium per sulphate in the aqueous medium. The spectroscopic characterizations during the formation of nanocomposites were studied using Attenuated total reflectance Fourier transform infrared (FTIR-ATR) spectroscopy, ultraviolet–visible spectrophotometer (Uv-Vis). Electrical conductivity of the emulsion solution was measured by Conductivity Meter from aqueous sample solution. Also, yield of the powder nanocomposites was measured. SDBS and SDS used for investigation of surfactant effect on yield, electrical conductivity and polymerization process. Determination of polymerization yield, (FTIR-ATR) and (Uv-Vis) prove that the SDBS surfactant become more incorporated into the conducting polymers and there is strong interaction between the [P(AN-co-MA)]-PPy derivatives which prepared by these surfactants. The similar inclusion of SDS into conducting polymers was not observed, there is a remarkable difference at nanocomposites which prepared with SDS.

Keywords: nanocomposites, core-shell, pyrole, surfactant

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Authors: Priyadarshini Kiran, Gulshan Kumar

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: Social media are becoming the most important tools for interaction among learners, pedagogues and parents where everybody can share, exchange, comment, discuss and create information and knowledge in a collaborative way. The present case study attempts to highlight the role of social media (WhatsApp) in nurturing learning habits in toddlers with the help of parents in primary education. The Case study is based on primary data collected from a primary school situated in a small town in the northern state of Uttar Pradesh, India. In research methodology, survey and structured interviews have been used as a tool collected from parents and pedagogues. The findings Suggest: - To nurture learning habits in toddlers, parents and pedagogues use social media site (WhatsApp) in real-time and that too is convenient and handy; - Skill enhancement on the part of Pedagogues as a result of employing innovative teaching-learning techniques; - Social media sites serve as a social connectivity tool to ward off negativity and monotony on the part of parents and pedagogues in the wake of COVID- 19

Keywords: innovative teaching-learning techniques, pedagogues, social media, nurture, toddlers

Procedia PDF Downloads 152

Authors: Darwin Junnior Sabino Diego, Brando Burgos Guerrero, Diego Arroyo Villanueva

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Additive manufacturing, commonly known as 3D printing, has revolutionized modern manufacturing by enabling the agile creation of complex objects. However, challenges persist in the consistency and quality of printed parts, particularly in their mechanical properties. This study focuses on addressing these challenges through the optimization of printing parameters in FDM technology, using Machine Learning techniques. Our aim is to improve the mechanical properties of printed objects by optimizing parameters such as speed, temperature, and orientation. We implement a methodology that combines experimental data collection with Machine Learning algorithms to identify relationships between printing parameters and mechanical properties. The results demonstrate the potential of this methodology to enhance the quality and consistency of 3D printed products, with significant applications across various industrial fields. This research not only advances understanding of additive manufacturing but also opens new avenues for practical implementation in industrial settings.

Keywords: 3D printing, additive manufacturing, machine learning, mechanical properties

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Authors: O. J. Jesumoroti, Faridoon, R. Klein, K. A. Iobb, D. Mnkadhla, H. C. Hoppe, P. T. Kaye

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The 1, 3-aryl diketo acids (DKA) based agents represent an important class of HIV integrase (IN) strand transfer inhibitors. In other to study the chelating role of the divalent metal ion in the inhibition of IN strand transfer, we designed and synthesized a series of 2-hydroxy-3-oxo-3-phenyl propionate derivatives with the notion that such compounds could interact with the divalent ion in the active site of IN. The synthetic sequence to the desired compounds involves the concept of Doebner knoevenagel condensation, Fischer esterification and ketohydroxylation using neuclophilic re-oxidant; compounds were characterized by their IR, IHNMR, 13CNMR, HRMS spectroscopic data and melting point determination. Also, molecular docking was employed in this study and it was revealed that there is interaction with the active site of the enzyme. However, there is disparity in the corresponding anti-HIV activity determined by the experimental bioassay. These compounds lack potency at low micromolar concentration when compared to the results of the docking studies. Nevertheless, the results of the study suggest modification of the aryl ring with one or two hydroxyl groups to improve the inhibitory activity.

Keywords: anti-HIV-1 integrase, ketohydroxylation, molecular docking, propionate derivatives

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Authors: Oluwayemisi O. Alaba, John O. Olaomi

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The 2013 Nigerian Demographic Health Survey (NDHS) data was used to investigate the determinants of family size in Nigeria using the geo-additive model. The fixed effect of categorical covariates were modelled using the diffuse prior, P-spline with second-order random walk for the nonlinear effect of continuous variable, spatial effects followed Markov random field priors while the exchangeable normal priors were used for the random effects of the community and household. The Negative Binomial distribution was used to handle overdispersion of the dependent variable. Inference was fully Bayesian approach. Results showed a declining effect of secondary and higher education of mother, Yoruba tribe, Christianity, family planning, mother giving birth by caesarean section and having a partner who has secondary education on family size. Big family size is positively associated with age at first birth, number of daughters in a household, being gainfully employed, married and living with partner, community and household effects.

Keywords: Bayesian analysis, family size, geo-additive model, negative binomial

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Authors: Somesh Misha, Smita Raghuvanshi, Suresh Gupta

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Increasing concentration of green house gases (GHG's), such as CO2 is of major concern and start showing its impact nowadays. The recent studies are focused on developing the continuous system using photoautotrophs for CO2 mitigation and simultaneous production of primary and secondary metabolites as a value addition. The advent of carbon concentrating mechanism had blurred the distinction between autotrophs and heterotrophs and now the paradigm has shifted towards the carbon capture and utilization (CCU) rather than carbon capture and sequestration (CCS). In the present work, a bioreactor was developed utilizing the chemolithotrophic bacterial species using CO2 mitigation and simultaneous value addition. The kinetic modeling was done and the biokinetic parameters are obtained for developing the bioreactor. The bioreactor was developed and studied for its operation and performance in terms of volumetric loading rate, mass loading rate, elimination capacity and removal efficiency. The characterization of effluent from the bioreactor was carried out for the products obtained using the analyzing techniques such as FTIR, GC-MS, and NMR. The developed bioreactor promised an economic, efficient and effective solution for CO2 mitigation and simultaneous value addition.

Keywords: CO2 mitigation, bio-reactor, chemolithotrophic bacterial species, FTIR, GC-MS, NMR

Procedia PDF Downloads 449

Authors: Pedro A. Marques, Francisco Monteiro, Alessandra Zumbo, Alessia Simonini, Miguel A. Mendez

Abstract:

Cryogenic fuels such as Liquid Hydrogen (LH₂) must be transported and stored at extremely low temperatures. Without expensive active cooling solutions, preventing fuel boil-off over time is impossible. Hence, one must resort to venting systems at the cost of significant energy and fuel mass loss. These losses increase significantly in propellant tanks installed on vehicles, as the presence of external accelerations induces sloshing. Sloshing increases heat and mass transfer rates and leads to significant pressure oscillations, which might further trigger propellant venting. To make LH₂ economically viable, it is essential to minimize these factors by using advanced control techniques. However, these require accurate modelling and a full understanding of the tank's thermodynamics. The present research aims to implement a simple thermodynamic model capable of predicting the state of a cryogenic fuel tank under different operating conditions (i.e., filling, pressurization, fuel extraction, long-term storage, and sloshing). Since this model relies on a set of closure parameters to drive the system's transient response, it must be calibrated using experimental or numerical data. This work focuses on the former approach, wherein the model is calibrated through an experimental campaign carried out on a reduced-scale model of a cryogenic tank. The thermodynamic model of the system is composed of three control volumes: the ullage, the liquid, and the insulating walls. Under this lumped formulation, the governing equations are derived from energy and mass balances in each region, with mass-averaged properties assigned to each of them. The gas-liquid interface is treated as an infinitesimally thin region across which both phases can exchange mass and heat. This results in a coupled system of ordinary differential equations, which must be closed with heat and mass transfer coefficients between each control volume. These parameters are linked to the system evolution via empirical relations derived from different operating regimes of the tank. The derivation of these relations is carried out using an inverse method to find the optimal relations that allow the model to reproduce the available data. This approach extends classic system identification methods beyond linear dynamical systems via a nonlinear optimization step. Thanks to the data-driven assimilation of the closure problem, the resulting model accurately predicts the evolution of the tank's thermodynamics at a negligible computational cost. The lumped model can thus be easily integrated with other submodels to perform complete system simulations in real time. Moreover, by setting the model in a dimensionless form, a scaling analysis allowed us to relate the tested configurations to a representative full-size tank for naval applications. It was thus possible to compare the relative importance of different transport phenomena between the laboratory model and the full-size prototype among the different operating regimes.

Keywords: destratification, hydrogen, modeling, pressure-drop, pressurization, sloshing, thermodynamics

Procedia PDF Downloads 78

Authors: Jingya Huang

Abstract:

This paper argues that Moushumi Mazoomdar has non-monogamous relationships with different men before and after her marriage as a form of rebellion against the traditional Indian culture deeply ingrained in her. Written by Jhumpa Lahiri, The Namesake (2004) features an Indian couple migrating to America who gives birth to two children, including the main character Gogol. Moushumi, like Gogol, is also a second-generation Indian American. Because of the influence of American culture, Moushumi prefers to marry for love, disdaining any thought of an arranged marriage. This paper is divided into two parts: before and after marriage which can also be seen in the light of polyamory and infidelity. First, according to Anapol (2010), polyamory is a newly created word from Greek and Latin which means “loving more than one person at a time when it comes to romantic or erotic love.” The discussion of polyamory mainly focuses on the most basic heterosexual relationship without mentioning of homosexual and bisexual love relationships. By adopting Anapol’s concept of polyamory, this paper examines the nature of the relationships between Moushumi and other men before her marriage. Afterwards, the concept of infidelity is discussed to analyze the interaction between Moushumi and Dimitri. How Moushumi rebels against tradition is shown through these two main discussions.

Keywords: Indian American, non-monogamous relationship, rebellion, polyamory, infidelity

Procedia PDF Downloads 324

Authors: H. Chassaigne, S. Gioria, J. Lobo Vicente, D. Carpi, P. Barboro, G. Tomasi, A. Kinsner-Ovaskainen, F. Rossi

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Emerging approaches in the area of exposure to nanomaterials and assessment of human health effects combine the use of in vitro systems and analytical techniques to study the perturbation of the proteome and/or the metabolome. We investigated the modification in the cytoplasmic compartment of the Balb/3T3 cell line exposed to gold nanoparticles. On one hand, the proteomic approach is quite standardized even if it requires precautions when dealing with in vitro systems. On the other hand, metabolomic analysis is challenging due to the chemical diversity of cellular metabolites that complicate data elaboration and interpretation. Differentially expressed proteins were found to cover a range of functions including stress response, cell metabolism, cell growth and cytoskeleton organization. In addition, de-regulated metabolites were annotated using the HMDB database. The "omics" fields hold huge promises in the interaction of nanoparticles with biological systems. The combination of proteomics and metabolomics data is possible however challenging.

Keywords: data processing, gold nanoparticles, in vitro systems, metabolomics, proteomics

Procedia PDF Downloads 485