Search results for: dimensional affect prediction

Authors: Judith Stein, Elfriede Friedmann

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The injection of a drug into the vitreous body for the treatment of retinal diseases like wet aged-related macular degeneration (AMD) is the most common medical intervention worldwide. We develop mathematical models for drug transport in the vitreous body of a human eye to analyse the impact of different rheological models of the vitreous on drug distribution. In addition to the convection diffusion equation characterizing the drug spreading, we use porous media modeling for the healthy vitreous with a dense collagen network and include the steady permeating flow of the aqueous humor described by Darcy's law driven by a pressure drop. Additionally, the vitreous body in a healthy human eye behaves like a viscoelastic gel through the collagen fibers suspended in the network of hyaluronic acid and acts as a drug depot for the treatment of retinal diseases. In a completely liquefied vitreous, we couple the drug diffusion with the classical Navier-Stokes flow equations. We prove the global existence and uniqueness of the weak solution of the developed initial-boundary value problem describing the drug distribution in the healthy vitreous considering the permeating aqueous humor flow in the realistic three-dimensional setting. In particular, for the drug diffusion equation, results from the literature are extended from homogeneous Dirichlet boundary conditions to our mixed boundary conditions that describe the eye with the Galerkin's method using Cauchy-Schwarz inequality and trace theorem. Because there is only a small effective drug concentration range and higher concentrations may be toxic, the ability to model the drug transport could improve the therapy by considering patient individual differences and give a better understanding of the physiological and pathological processes in the vitreous.

Keywords: coupled PDE systems, drug diffusion, mixed boundary conditions, vitreous body

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Authors: Michael Brazley

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Virtual Reality (VR) and 3D videos are the most current generation of learning technology today. Virtual Reality and 3D videos are being used in professional offices and Schools now for marketing and education. Technology in the field of design has progress from two dimensional drawings to 3D models, using computers and sophisticated software. Virtual Reality is being used as collaborative means to allow designers and others to meet and communicate inside models or VR platforms using avatars. This research proposes to teach students from different backgrounds how to take a digital model into a 3D video, then into VR, and finally VR with multiple avatars communicating with each other in real time. The next step would be to develop the model where people from three or more different locations can meet as avatars in real time, in the same model and talk to each other. This research is longitudinal, studying the use of 3D videos in graduate design and Virtual Reality in XR (Extended Reality) courses. The research methodology is a combination of quantitative and qualitative methods. The qualitative methods begin with the literature review and case studies. The quantitative methods come by way of student’s 3D videos, survey, and Extended Reality (XR) course work. The end product is to develop a VR platform with multiple avatars being able to communicate in real time. This research is important because it will allow multiple users to remotely enter your model or VR platform from any location in the world and effectively communicate in real time. This research will lead to improved learning and training using Virtual Reality and Avatars; and is generalizable because most Colleges, Universities, and many citizens own VR equipment and computer labs. This research did produce a VR platform with multiple avatars having the ability to move and speak to each other in real time. Major implications of the research include but not limited to improved: learning, teaching, communication, marketing, designing, planning, etc. Both hardware and software played a major role in project success.

Keywords: virtual reality, avatars, education, XR

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Authors: Levente Kovács, Fruzsina Luca Kézér, Ottó Szenci

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Prediction of the onset of calving and recognizing difficulties at calving has great importance in decreasing neonatal losses and reducing the risk of health problems in the early postpartum period. In this study, changes of rumination time, reticuloruminal pH and temperature were investigated in eutocic (EUT, n = 10) and dystocic (DYS, n = 8) dairy cows around parturition. Rumination time was continuously recorded using an acoustic biotelemetry system, whereas reticuloruminal pH and temperature were recorded using an indwelling and wireless data transmitting system. The recording period lasted from 3 d before calving until 7 days in milk. For the comparison of rumination time and reticuloruminal characteristics between groups, time to return to baseline (the time interval required to return to baseline from the delivery of the calf) and area under the curve (AUC, both for prepartum and postpartum periods) were calculated for each parameter. Rumination time decreased from baseline 28 h before calving both for EUT and DYS cows (P = 0.023 and P = 0.017, respectively). After 20 h before calving, it decreased onwards to reach 32.4 ± 2.3 and 13.2 ± 2.0 min/4 h between 8 and 4 h before delivery in EUT and DYS cows, respectively, and then it decreased below 10 and 5 min during the last 4 h before calving (P = 0.003 and P = 0.008, respectively). Until 12 h after delivery rumination time reached 42.6 ± 2.7 and 51.0 ± 3.1 min/4 h in DYS and EUT dams, respectively, however, AUC and time to return to baseline suggested lower rumination activity in DYS cows than in EUT dams for the 168-h postpartum observational period (P = 0.012 and P = 0.002, respectively). Reticuloruminal pH decreased from baseline 56 h before calving both for EUT and DYS cows (P = 0.012 and P = 0.016, respectively), but did not differ between groups before delivery. In DYS cows, reticuloruminal temperature decreased from baseline 32 h before calving by 0.23 ± 0.02 °C (P = 0.012), whereas in EUT cows such a decrease was found only 20 h before delivery (0.48 ± 0.05 °C, P < 0.01). AUC of reticuloruminal temperature calculated for the prepartum period was greater in EUT cows than in DYS cows (P = 0.042). During the first 4 h after calving, it decreased from 39.7 ± 0.1 to 39.00 ± 0.1 °C and from 39.8 ± 0.1 to 38.8 ± 0.1 °C in EUT and DYS cows, respectively (P < 0.01 for both groups) and reached baseline levels after 35.4 ± 3.4 and 37.8 ± 4.2 h after calving in EUT and DYS cows, respectively. Based on our results, continuous monitoring of changes in rumination time and reticuloruminal temperature seems to be promising in the early detection of cows with a higher risk of dystocia. Depressed postpartum rumination time of DYS cows highlights the importance of the monitoring of cows experiencing difficulties at calving.

Keywords: reticuloruminal pH, reticuloruminal temperature, rumination time, dairy cows, dystocia

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Authors: Prama Mukhopadhyay

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Starting from transport to food, today’s world platform economy and digital markets have taken over almost every sphere of consumers’ lives. Sellers and buyers are getting connected through platforms, which is acting as an intermediary. It has made consumer’s life easier in terms of time, price, choice and other factors. Having said that, there are several concerns regarding platforms. There are competition law concerns like unfair pricing, deep discounting by the platforms which affect the consumer welfare. Apart from that, the biggest problem is lack of transparency with respect to the business models, how it operates, price calculation, etc. In most of the cases, consumers are unaware of how their personal data are being used. In most of the cases, they are unaware of how algorithm uses their personal data to determine the price of the product or even to show the relevant products using their previous searches. Using personal or non-personal data without consumer’s consent is a huge legal concern. In addition to this, another major issue lies with the question of liability. If a dispute arises, who will be responsible? The seller or the platform? For example, if someone ordered food through a food delivery app and the food was bad, in this situation who will be liable: the restaurant or the food delivery platform? In this paper, the researcher tries to examine the legal concern related to platform economy from the consumer protection and consumer welfare perspectives. The paper analyses the cases from different jurisdictions and approach taken by the judiciaries. The author compares the existing legislation of EU, US and other Asian Countries and tries to highlight the best practices.

Keywords: competition, consumer, data, platform

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Authors: Mithil Pandey, Ragunathan Bala Subramanian

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One of the major conversion technologies in the oil refinery industry is Fluid catalytic cracking (FCC) which produces the majority of the world’s gasoline. Some useful products are generated from the vacuum gas oil, heavy gas oil and residue feedstocks by the FCC unit in an oil refinery. Moreover, Zeolite catalysts (zeo-catalysts) have found widespread applications and have proved to be substantial and paradigmatic in oil refining and petrochemical processes, such as FCC because of their porous features. Several famous zeo-catalysts have been fabricated and applied in industrial processes as milestones in history, and have brought on huge changes in petrochemicals. So far, more than twenty types of zeolites have been industrially applied, and their versatile porous architectures with their essential features have contributed to affect the catalytic efficiency. This poster depicts the evolution of pore models in zeolite catalysts which are accompanied by an increase in environmental and demands. The crucial roles of modulating pore models are outlined for zeo-catalysts for the enhancement of their catalytic performances in various industrial processes. The development of industrial processes for the FCC process, aromatic conversions and olefin production, makes it obvious that the pore architecture plays a very important role in zeo-catalysis processes. By looking at the different necessities of industrial processes, rational construction of the pore model is critically essential. Besides, the pore structure of the zeolite would have a substantial and direct effect on the utilization efficiency of the zeo-catalyst.

Keywords: catalysts, fluid catalytic cracking, industrial processes, zeolite

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Authors: Omran Alharbi, Victor Lally

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In recent decades, a number of educational institutions around the world have come to depend on technology such as the Blackboard system to improve their educational environment. On the other hand, there are many factors that delay the usage of this technology, especially in developing nations such as Saudi Arabia. The goal of this study was to investigate learner’s views of the use of Blackboard in one Saudi university in order to gain a comprehensive view of the factors that delay the implementation of technology in Saudi institutions. This study utilizes a qualitative approach, with data being collected through semi-structured interviews. Six participants from different disciplines took part in this study. The findings indicated that there are two levels of factors that affect students’ use of the Blackboard system. These are factors at the institutional level, such as lack of technical support and lack of training support, which lead to insufficient training related to the Blackboard system. The second level of factors is at the individual level, for example, a lack of teacher motivation and encouragement. In addition, students do not have sufficient levels of skills or knowledge related to how to use the Blackboard in their learning. Conclusion: learners confronted and faced two main types of factors (at the institution level and individual level) that delayed and impeded their learning. Institutions in KSA should take steps and implement strategies to remove or reduce these factors in order to allow students to benefit from the latest technology in their learning.

Keywords: blackboard, factors, KSA, learners

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Authors: N. D. Iswarya, M. A. Maluk Mohamed, N. Vijaya

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Grid is infrastructure that allows the deployment of distributed data in large size from multiple locations to reach a common goal. Scheduling data intensive applications becomes challenging as the size of data sets are very huge in size. Only two solutions exist in order to tackle this challenging issue. First, computation which requires huge data sets to be processed can be transferred to the data site. Second, the required data sets can be transferred to the computation site. In the former scenario, the computation cannot be transferred since the servers are storage/data servers with little or no computational capability. Hence, the second scenario can be considered for further exploration. During scheduling, transferring huge data sets from one site to another site requires more network bandwidth. In order to mitigate this issue, this work focuses on incorporating cognitive science in scheduling. Cognitive Science is the study of human brain and its related activities. Current researches are mainly focused on to incorporate cognitive science in various computational modeling techniques. In this work, the problem solving approach of human brain is studied and incorporated during the data intensive scheduling in grid environments. Here, a cognitive engine is designed and deployed in various grid sites. The intelligent agents present in CE will help in analyzing the request and creating the knowledge base. Depending upon the link capacity, decision will be taken whether to transfer data sets or to partition the data sets. Prediction of next request is made by the agents to serve the requesting site with data sets in advance. This will reduce the data availability time and data transfer time. Replica catalog and Meta data catalog created by the agents assist in decision making process.

Keywords: data grid, grid workflow scheduling, cognitive artificial intelligence

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Authors: M. Hetmańczyk, R. Polaniak, K. Brukało, E. Grochowska-Niedworok

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Eating behaviours of people are determined by knowledge gained at different stages of life. Children’s diet is especially important. They have to eat meals regularly. Meals should consist of protein, carbohydrates and fat, and drinking the right amount of water. Mistakes in children’s diets affect their health and may lead to health issues such as diabetes, overweight, obesity or malnutrition. The aim of the study was to assess the eating habits among 10-15-year-old children. To achieve this aim, the study included children aged 10-15 years living in Silesia Province, Poland; the participants consisted of 52.08% girls and 47.92% boys. Authorial questionnaire contains 28 questions about eating habits. The results of 192 students were subjected to analysis. The results show that half of the surveyed students participated in physical activity every day. Most children ate 4-5 meals every day, but the breaks between them were too long (four and more hours). Children generally ate cooked meals. Most children ate first breakfast every day, but only one third of studied children ate a second breakfast daily, while 93.75% ate vegetables at least once a day, 94.79% ate fruit at least once a day, and 79.17% drink a daily glass of milk or more. The study found that the eating behaviours of the surveyed children were unsatisfying. While the children did not participate in physical activity often enough, girls took part slightly more often. Children eat second breakfast not often enough. Younger children (10-12 years old) are doing it more often than the older children (13-15 years old). Gender is not a determinant of the frequency of second breakfast consumption.

Keywords: eating habits, children, diet, nutrition status

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Authors: Khalid S. Hashim, Andy Shaw, Rafid Alkhaddar, Montserrat Ortoneda Pedrola

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A flow column has been innovatively used in the design of a new electrocoagulation reactor (ECR1) that will reduce the temperature of water being treated; where the flow columns work as a radiator for the water being treated. In order to investigate the performance of ECR1 and compare it to that of traditional reactors; 600 mL water samples with an initial temperature of 35 0C were pumped continuously through these reactors for 30 min at current density of 1 mA/cm2. The temperature of water being treated was measured at 5 minutes intervals over a 30 minutes period using a thermometer. Additional experiments were commenced to investigate the effects of initial temperature (15-35 0C), water conductivity (0.15 – 1.2 S) and current density (0.5 -3 mA/cm2) on the performance of ECR1. The results obtained demonstrated that the ECR1, at a current density of 1 mA/cm2 and continuous flow model, reduced water temperature from 35 0C to the vicinity of 28 0C during the first 15 minutes and kept the same level till the end of the treatment time. While, the temperature increased from 28.1 to 29.8 0C and from 29.8 to 31.9 0C in the batch and the traditional continuous flow models respectively. In term of initial temperature, ECR1 maintained the temperature of water being treated within the range of 22 to 28 0C without the need for external cooling system even when the initial temperatures varied over a wide range (15 to 35 0C). The influent water conductivity was found to be a significant variable that affect the temperature. The desirable value of water conductivity is 0.6 S. However, it was found that the water temperature increased rapidly with a higher current density.

Keywords: water temperature, flow column, electrocoagulation

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Authors: Qiaohui Zhong, Yiqi Kuang, Wanxun Cai, Libin Huang

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As a community public facility, the popularity and perfection of old clothes recycling products directly affect people's impression of the whole city, which is related to the happiness index of residents' lives and is of great significance to the construction of eco-civilized cities and the realization of sustainable urban development. At present, China's waste clothing is characterized by large production and a high utilization rate, but the current rate of old clothes recycling is low, and the ‘one-size-fits-all’ recycling model makes people's motivation for old clothes recycling low, and old clothes recycling is in a dilemma. Based on the two online and offline recycling modes of old clothes recycling in Chinese communities, this paper conducts an in-depth survey on the public, operators, and regulators from the aspects of activity scene analysis, crowd attributes analysis, and community space analysis summarizes the difficulties of old clothes recycling for the public - nowhere to recycle, inconvenient to recycle and unwilling to recycle, and analyzes the factors that lead to these difficulties, and gives a solution with foreign experience to solve these problems. It also analyzes the factors that lead to these difficulties and gives targeted suggestions in combination with foreign experience, exploring and proposing a set of appropriate modern old-clothes recycling modes.

Keywords: community, old clothes recycling, recycling mode, sustainable urban development

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Authors: Maedeh Gharazi

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Adults with age 50 and older will include more than 70% of the diabetic populace by the year 2025. More established patients with diabetes are more inclined to have concurrent ceaseless conditions like hypertension, dyslipidemia, and cardiovascular sickness that may affect their nutritious necessities. The issue of achievement and support of an ideal body weight in elderly diabetic persons may not be as direct as in other age gatherings, and the risk-benefit ratio may be diverse too. Albeit expanded predominance of overweight and weight in the elderly adds to insulin resistance and hyperglycemia, more seasoned tenants of long haul care offices who experience the ill effects of diabetes have a tendency to be underweight. Both may mean insufficient nutritional status and lead to expanded grimness and mortality. The attendant problems of appetite changes, palatability of food, dietary restrictions, loneliness, and depression may influence the sort and amount of food devoured by elderly persons. Organized screening devices may recognize nutrition related issues that warrant proof based mediations. Despite the fact that glucose control and health concerns are essential calculates diet change in the more established populace, different contemplations incorporate personal satisfaction and individual inclinations. Redoing of nutritious rules to the needs of the more seasoned diabetic patient bodes well.

Keywords: diabetes, nutritious necessities, insulin resistance, glucose control

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Authors: Rim Frikha, Maha Ben Jema, Moez Elloumi, Tarek Rebai

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Background: Acute lymphoblastic leukemia (ALL); a common blood cancer characterized by the interaction between genetic and environmental factors. Methylenetetrahydrofolate reductase (MTHFR) is an essential folate metabolic enzyme in the processes of DNA synthesis and methylation. A common functional variant of the MTHFR gene, the A1298C, which induces disturbances in folate metabolism, may affect susceptibility to ALL. Objective: The present study aimed to assess the prevalence of MTHFR polymorphism A1298 > C in Tunisian children with ALL. Materials and Methods: A total of 28 Tunisian ALL children were enrolled in this study. Genomic DNA was extracted from whole venous blood collected in ethylenediaminetetraacetic acid (EDTA). Genotyping was carried out with restriction fragment length polymorphism (RFLP) using MboII restriction enzyme. Genotype distribution and allele frequency of MTHFR A1298C was calculated in ALL patients. Results: The A1298C variant of MTHFR was found in 11(19.6%) heterozygous and one homozygous patient (3.5%). Conclusions: This result highlights that A1298C polymorphism of MTHFR is common in Tunisian childhood ALL and suggests that this variant may have a potential role in leukemogenesis. Genotyping of large samples and different ethnicities are required to validate these findings.

Keywords: methylenetetrahydrofolate reductase, acute lymphoblastic leukemia, A1298C variant, prevalence

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Authors: Didier Auroux, Vladimir Groza

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This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.

Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization

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Authors: Okhee Woo

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Purpose: With increasing concern of individual radiation exposure doses, studies analyzing radiation dosage in breast imaging modalities are required. Aim of this study is to compare radiation dosage and image quality between digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM). Methods and Materials: 303 patients (mean age 52.1 years) who studied DBT and FFDM were retrospectively reviewed. Radiation dosage data were obtained by radiation dosage scoring and monitoring program: Radimetrics (Bayer HealthCare, Whippany, NJ). Entrance dose and mean glandular doses in each breast were obtained in both imaging modalities. To compare the image quality of DBT with two-dimensional synthesized mammogram (2DSM) and FFDM, 5-point scoring of lesion clarity was assessed and the better modality between the two was selected. Interobserver performance was compared with kappa values and diagnostic accuracy was compared using McNemar test. The parameters of radiation dosages (entrance dose, mean glandular dose) and image quality were compared between two modalities by using paired t-test and Wilcoxon rank sum test. Results: For entrance dose and mean glandular doses for each breasts, DBT had lower values compared with FFDM (p-value < 0.0001). Diagnostic accuracy did not have statistical difference, but lesion clarity score was higher in DBT with 2DSM and DBT was chosen as a better modality compared with FFDM. Conclusion: DBT showed lower radiation entrance dose and also lower mean glandular doses to both breasts compared with FFDM. Also, DBT with 2DSM had better image quality than FFDM with similar diagnostic accuracy, suggesting that DBT may have a potential to be performed as an alternative to FFDM.

Keywords: radiation dose, DBT, digital mammography, image quality

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Authors: J. Zekri, N. Souilah, W. Abdelaziz, D. Alatou

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Our study shall focus on the ability of trees cork oak that showed vis-à-vis sensitivity to climate change, including late spring frosts. The combination of these factors resulted in damage alarmed, therefore forest ecosystems weakened trees that can affect their ability to support other abiotic and biotic stresses, For this we tested its tolerance to thermal variations and cold weather conditions by estimating some stress markers (quantification of proteins, RNA, soluble sugars) that are quantified to evaluate the cold tolerance of seedlings. Sowing of cork oak (Quercus suber L.) is grown in controlled conditions at 25° C ± 2° C in long days 16h. These seedlings are transferred at low temperatures between 5° C and -6° C for a period of 3 hours. Biochemical analyzes were performed in the various organs of the cork oak seedlings. Cool temperatures induced a significant accumulation of proline in different organs of seedlings and the optimum concentrations were observed in the roots with very high concentrations (4 times larger than those of the control). The accumulation of soluble sugars is significantly in stems and roots at 0° C. Protein concentrations are very high in leaves of both growth and high waves in rod at -4° C to -2° C. Tolerance cork oak seems to be at the thermal limit of -2°C. The concentration of these metabolites in the various organs showed the ability oak cork hardening during the winter.

Keywords: climate change, thermal change, semi-aride, biochemical markers, heat stress

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Authors: Saeko Takahashi, Kazuo Hiraki

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Is it more fun to watch videos together than watching alone? Previous studies showed that synchronizing with others enhances subsequent prosocial behavior and affiliation, and conversely, prosocial individuals tend to coordinate with a partner to a greater extent. However, compared to adults, less is known about interpersonal coordination of young children in real-life situations because most studies have focused on children’s particular movement using specific tools or tasks in a laboratory setting. It has also been unclear if prosociality of young children affect the extent of interpersonal coordination within dyads. The present study examined data from motion capture of five body parts of 4-year-old dyads watching the same stimuli together or alone. A questionnaire survey including participants’ prosocial trait was also conducted. The wavelet coherence of each body parts within dyads was calculated as a measure of the extent of interpersonal coordination. Results showed that the dyads became significantly more coordinated in a social situation compared to a non-social situation. Moreover, dyads with averagely higher prosociality were more coordinated. These results shed some light on the development of interpersonal coordination in terms of social ability in young children. This study also offers a useful method for a study of spontaneous coordination in young children and infants without instructions or verbal responses.

Keywords: child development, interpersonal coordination, prosociality, synchrony, wavelet transform

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Authors: Idris M. Olatunde, Kareem B.

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In manufacturing systems, especially job shops, service performance is a key factor that determines customer satisfaction. Service performance depends not only on the quality of the output but on the delivery lead times as well. Besides product quality enhancement, delivery lead time must be minimized for optimal patronage. Quoting accurate due dates is sine quo non for job shop operational survival in a global competitive environment. Quoting accurate due dates in job shops has been a herculean task that nearly defiled solutions from many methods employed due to complex jobs routing nature of the system. This class of NP-hard problems possessed no rigid algorithms that can give an optimal solution. Jobshop operational problem is more complex in developing nations due to some peculiar factors. Operational complexity in job shops emanated from political instability, poor economy, technological know-how, and the non-promising socio-political environment. The mentioned exogenous factors were hardly considered in the previous studies on scheduling problem related to due date determination in job shops. This study has filled the gap created in the past studies by developing a dynamic model that incorporated the exogenous factors for accurate determination of due dates for varying jobs complexity. Real data from six job shops selected from the different part of Nigeria, were used to test the efficacy of the model, and the outcomes were analyzed statistically. The results of the analyzes showed that the model is more promising in determining accurate due dates than the traditional models deployed by many job shops in terms of patronage and lead times minimization.

Keywords: due dates prediction, improved performance, customer satisfaction, dynamic model, exogenous factors, job shops

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Authors: Saleem Z. Ramadan

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This paper discusses the effects of using progressive Type-I right censoring on the design of the Simple Step Accelerated Life testing using Bayesian approach for Weibull life products under the assumption of cumulative exposure model. The optimization criterion used in this paper is to minimize the expected pre-posterior variance of the PTH percentile time of failures. The model variables are the stress changing time and the stress value for the first step. A comparison between the conventional and the progressive Type-I right censoring is provided. The results have shown that the progressive Type-I right censoring reduces the cost of testing on the expense of the test precision when the sample size is small. Moreover, the results have shown that using strong priors or large sample size reduces the sensitivity of the test precision to the censoring proportion. Hence, the progressive Type-I right censoring is recommended in these cases as progressive Type-I right censoring reduces the cost of the test and doesn't affect the precision of the test a lot. Moreover, the results have shown that using direct or indirect priors affects the precision of the test.

Keywords: reliability, accelerated life testing, cumulative exposure model, Bayesian estimation, progressive type-I censoring, Weibull distribution

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Authors: Mary Joy C. Montenegro, Voltaire M. Mistades

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This action research was implemented to enhance the teaching of linear motion and to improve students' conceptual understanding and engagement using a developed 7R-based module called 'module on vectors and one-dimensional kinematics' (MVOK). MVOK was validated in terms of objectives, contents, format, and language used, presentation, usefulness, and overall presentation. The validation process revealed a value of 4.7 interpreted as 'Very Acceptable' with a substantial agreement (0. 60) from the validators. One intact class of 46 Grade 12 STEM students from one of the public schools in Paranaque City served as the participants of this study. The students were taught using the module during the first semester of the academic year 2019–2020. Employing the mixed-method approach, quantitative data were gathered using pretest/posttest, activity sheets, problem sets, and survey form, while qualitative data were obtained from surveys, interviews, observations, and reflection log. After the implementation, there was a significant difference of 18.4 on students’ conceptual understanding as shown in their pre-test and post-test scores on the 24-item test with a moderate Hake gain equal to 0.45 and an effect size of 0.83. Moreover, the scores on activity and problem sets have a 'very good' to 'excellent' rating, which signifies an increase in the level of students’ conceptual understanding. There also exists a significant difference between the mean scores of students’ engagement overall (t= 4.79, p = 0.000, p < 0.05) and in the dimension of emotion (t = 2.51, p = 0.03) and participation/interaction (t = 5.75, p = 0.001). These findings were supported by gathered qualitative data. Positive views were elicited from the students since it is an accessible tool for learning and has well-detailed explanations and examples. The results of this study may substantiate that using MVOK will lead to better physics content understanding and higher engagement.

Keywords: conceptual understanding, engagement, linear motion, module

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Authors: Hanei Son

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Since the beginning of the 2010s, ‘start-up boom’ has continued with the creation of many new enterprises in Korea. Such tendency was led by various changes in society such as emergence and diffusion of smartphones. Especially, the Korean government has been interested in start-ups and entrepreneurship as an alternative engine for Korea's economic growth. With strong support from the government, as a result, many new enterprises have been established for recent years and the Korean government seems to have achieved its goal: expanding the basis of start-ups. However, it is unclear which factors affect the survival and growth of these new enterprises after their creation. Therefore, this study aims to identify which start-ups from early 2010s survived and which factors influenced their survival and growth. The study will strongly focus on which industries the new enterprises were in, as environmental elements are expected to be critical factors for business of start-ups in Korean context. For this purpose, 105 companies which were introduced as high potential start-ups from 2010 to 2012 were considered in the analysis. According to their current status, dead or alive, the start-ups were categorized by their industries and service area. Through this analysis, it was observed that many start-ups that are still in business are in internet or mobile platform businesses and four major sectors. In each group, a representative case has been studied to reveal its survival and growth factors. The results point to the importance of industrial characteristics for the survival and success of Korean startups and offer political implications in which sector and business more potentials for start-ups in Korea lie in.

Keywords: government support for start-ups, industrial characteristics, Korean start-ups, survival of start-ups

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Authors: B. Adcock, H. van Rensburg

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Education is ever-changing to keep up with innovative technological development and the rapid acceleration of globalisation. This chapter introduces the historical development and transformation of teaching in distance education from correspondence to on-line learning in Queensland universities. It furthermore investigates changes to the delivery models of distance education that have impacted on teaching at tertiary level in Queensland, and reflects on the social changes that have taken place during the past 100 years. This includes an analysis of the following five different periods in time: Foundation period (1911-1919) including World War I; 1920-1939 including the Great Depression; 1940-1970s, including World War II and the post war reconstruction; and the current technological era (1980s to present). In Queensland, the concept of distance education was begun by the University of Queensland (UQ) in 1911, when it began offering extension courses. The introduction of modern technology, in the form of electronic delivery, dramatically changed tertiary distance education due to political initiatives. The inclusion of electronic delivery in education signifies change at many levels, including policy, pedagogy, curriculum and governance. Changes in delivery not only affect the way study materials are delivered, but also the way courses are be taught and adjustments made by academics to their teaching methods.

Keywords: distance education, innovative technological development, on line education, tertiary education

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Authors: Wei Zhang, Yan He, Yan Wang, Yufeng Li, Chuanpeng Hao

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Surface roughness is an important index for evaluating surface quality, needs to be accurately measured to ensure the performance of the workpiece. The roughness measurement based on machine vision involves various image features, some of which are redundant. These redundant features affect the accuracy and speed of the visual approach. Previous research used correlation analysis methods to select the appropriate features. However, this feature analysis is independent and cannot fully utilize the information of data. Besides, blindly reducing features lose a lot of useful information, resulting in unreliable results. Therefore, the focus of this paper is on providing a redundant feature removal approach for visual roughness measurement. In this paper, the statistical methods and gray-level co-occurrence matrix(GLCM) are employed to extract the texture features of machined images effectively. Then, the principal component analysis(PCA) is used to fuse all extracted features into a new one, which reduces the feature dimension and maintains the integrity of the original information. Finally, the relationship between new features and roughness is established by the support vector machine(SVM). The experimental results show that the approach can effectively solve multi-feature information redundancy of machined surface images and provides a new idea for the visual evaluation of surface roughness.

Keywords: feature analysis, machine vision, PCA, surface roughness, SVM

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Authors: Gajanan M. Sonwane

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Nowadays, the entire pharmaceutical industry is facing the challenge of increasing efficiency and innovation. The major hurdles are the growing cost of research and development and a concurrent stagnating number of new chemical entities (NCEs). Hence, the challenge is to select the most druggable targets and to search the equivalent drug-like compounds, which also possess specific pharmacokinetic and toxicological properties that allow them to be developed as drugs. The present research work includes the studies of developing new anticancer heterocycles by using molecular modeling techniques. The heterocycles synthesized through such methodology are much effective as various physicochemical parameters have been already studied and the structure has been optimized for its best fit in the receptor. Hence, on the basis of the literature survey and considering the need to develop newer anticancer agents, new phenazinamine derivatives were designed by subjecting the nucleus to molecular modeling, viz., GQSAR analysis and docking studies. Simultaneously, these designed derivatives were subjected to in silico prediction of biological activity through PASS studies and then in silico toxicity risk assessment studies. In PASS studies, it was found that all the derivatives exhibited a good spectrum of biological activities confirming its anticancer potential. The toxicity risk assessment studies revealed that all the derivatives obey Lipinski’s rule. Amongst these series, compounds 4c, 5b and 6c were found to possess logP and drug-likeness values comparable with the standard Imatinib (used for anticancer activity studies) and also with the standard drug methotrexate (used for antimitotic activity studies). One of the most notable mutations is the threonine to isoleucine mutation at codon 315 (T315I), which is known to be resistant to all currently available TKI. Enzyme assay planned for confirmation of target selective activity.

Keywords: drug design, tyrosine kinases, anticancer, Phenazinamine

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Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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Authors: Yun Hang Stanley Cheung

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In recent years, many educators and entrepreneurs have often suggested that students’ and workers’ ability of the adversity response is very important, it would affect problem-solving strategies and ultimate success in their career or life. The meaning of resilience is discussed as the process of bouncing back and the ability to adapt well in adversity’s response, being resilient does not mean to live without any stress and difficulty, but to grow and thrive under pressure. The purpose of this study is to describe the process of resilience and adversity’s response. The use of the narrative inquiry aims for understanding the experiential process of adversity response, and the problem-solving strategies (such as emotion control, motivation, decisions making process), as well as making the experience become life story, which may be evaluated by its teller and its listeners. The narrative study describes the researcher’s self-experience of adversity’s response to the recovery of the seriously burnt injury from a hill fire at his 12 years old, as well as the adversities and obstacles related to the tragedy after the physical recovery. Sense-Making Theory and McCormack’s Lenses were used for constructive perspective and data analyzing. To conclude, this study has described the life story of fighting the adversities, also, those narratives come out some suggestions, which point out positive thinking is necessary to build up resilience and the ability of immediate adversity response. Also, some problem-solving strategies toward adversities are discussed, which are helpful for resilience education for youth and young adult.

Keywords: adversity response, life story, narrative inquiry, resilience

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Authors: Edson Vengesai

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Derivative products have become essential instruments in portfolio diversification, price discovery, and, most importantly, risk hedging. Derivatives are complex instruments; their valuation, volatility implications, and real impact on the underlying assets' behaviour are not well understood. Little is documented empirically, with conflicting conclusions on how these instruments affect firm risk exposures. Given the growing interest in using derivatives in risk management and portfolio engineering, this study examines the practical impact of derivative usage on the underlying stock price exposure and systematic risk. The paper uses data from South African listed firms. The study employs GARCH models to understand the effect of derivative uses on conditional stock volatility. The GMM models are used to estimate the effect of derivatives use on stocks' systematic risk as measured by Beta and on the total risk of stocks as measured by the standard deviation of returns. The results provide evidence on whether derivatives use is instrumental in reducing stock returns' systematic and total risk. The results are subjected to numerous controls for robustness, including financial leverage, firm size, growth opportunities, and macroeconomic effects.

Keywords: derivatives use, hedging, volatility, stock price exposure

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Authors: K. Geetha Ramesh, A. Ramachandraiah

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In an internal building space, daylight becomes a powerful source of illumination. The challenge therefore, is to develop means of utilizing both direct and diffuse natural light in buildings while maintaining and improving occupant's visual comfort, particularly at greater distances from the windows throwing daylight. The geometrical features of windows in a building have significant effect in providing daylight. The main goal of this research is to develop an innovative window geometry, which will effectively provide the daylight component adequately together with internal reflected component(IRC) and also the external reflected component(ERC), if any. This involves exploration of a light redirecting system using fractal geometry for windows, in order to penetrate and distribute daylight more uniformly to greater depths, minimizing heat gain and glare, and also to reduce building energy use substantially. Of late the creation of fractal geometrical window and the occurrence of daylight illuminance due to such windows is becoming an interesting study. The amount of daylight can change significantly based on the window geometry and sky conditions. This leads to the (i) exploration of various fractal patterns suitable for window designs, and (ii) quantification of the effect of chosen fractal window based on the relationship between the fractal pattern, size, orientation and glazing properties for optimizing daylighting. There are a lot of natural lighting applications able to predict the behaviour of a light in a room through a traditional opening - a regular window. The conventional prediction methodology involves the evaluation of the daylight factor, the internal reflected component and the external reflected component. Having evaluated the daylight illuminance level for a conventional window, the technical performance of a fractal window for an optimal daylighting is to be studied and compared with that of a regular window. The methodologies involved are highlighted in this paper.

Keywords: daylighting, fractal geometry, fractal window, optimization

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Authors: Nelson Andres, Meeko C. Masangcap, John Denver D. Catapang

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Balanga City as, the heart of Bataan, is a growing City and is now at its fast pace of development. The growth of commerce in the city results to an increase in commuters who travel back and forth through the city, leading to congestions. Consequently, queuing of vehicles along national roads and even in the highways of the city have become a regular occurrence. This common scenario of commuters flocking the city, private and public vehicles going bumper to bumper, especially during the rush hours, greatly affect the flow of traffic vehicles and is now a burden not only to the commuters but also to the government who is trying to address this dilemma. Seeing these terrible events, the implementation of an elevated Automated Guide-way transit is seen as a possible solution to help in the decongestion of the affected parts of Balanga City.In response to the problem, the researchers identify if it is feasible to have an elevated guide-way transit in the vicinity of Sapphire Street in Balanga City, Bataan. Specifically, the study aims to determine who will be the riders based on the demographic profile, where the trip can be generated and distributed, the time when volume of people usually peaks and the estimated volume of passengers. Statistical analysis is applied to the data gathered to find out if there is an important relationship between the demographic profile of the respondents and their preference of having an elevated railway transit in the City of Balanga.

Keywords: ridership, AGT, railway, elevated track

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Authors: Esra Turker, Umit Hakan Yildiz, Ahu Arslan Yildiz

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The key of regenerative medicine is mimicking natural three dimensional (3D) microenvironment of tissues by utilizing appropriate biomaterials. In this study, a synthetic biodegradable polymer; poly (L-lactide-co-ε-caprolactone) (PLLCL) and a natural polymer; collagen was used to mimic the biochemical structure of the natural extracellular matrix (ECM), and by means of electrospinning technique the real physical structure of ECM has mimicked. PLLCL/Collagen biocomposite scaffolds enables cell attachment, proliferation and nutrient transport through fabrication of micro to nanometer scale nanofibers. Biocomposite materials are commonly preferred due to limitations of physical and biocompatible properties of natural and synthetic materials. Combination of both materials improves the strength, degradation and biocompatibility of scaffold. Literature studies have shown that collagen is mostly solved with heavy chemicals, which is not suitable for cell culturing. To overcome this problem, a new approach has been developed in this study where polyvinylpyrrolidone (PVP) is used as co-electrospinning agent. PVP is preferred due to its water solubility, so PLLCL/collagen biocomposite scaffold can be easily and rapidly produced. Hydrolytic and enzymatic biodegradation as well as mechanical strength of scaffolds were examined in vitro. Cell adhesion, proliferation and cell morphology characterization studies have been performed as well. Further, on-chip drug screening analysis has been performed over 3D tumor models. Overall, the developed biocomposite scaffold was used for 3D tumor model formation and obtained results confirmed that developed model could be used for drug screening studies to predict clinical efficacy of a drug.

Keywords: biomaterials, 3D cell culture, drug screening, electrospinning, lab-on-a-chip, tissue engineering

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Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

Procedia PDF Downloads 85