Search results for: learner motivation model

Authors: Phan Minh Trang, Joacim Rocklöv, Kim Bao Giang, Gunnar Kullgren, Maria Nilsson

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There are recent studies from high income countries reporting an association between heat waves and hospital admissions for mental health disorders. It is not previously studied if such relations exist in sub-tropical and tropical low- and middle-income countries. In this study from Vietnam, the assumption was that hospital admissions for mental disorders may be triggered, or exacerbated, by heat exposure and heat waves. A database from Hanoi Mental Hospital with mental disorders diagnosed by the International Classification of Diseases 10, spanning over five years, was used to estimate the heatwave-related impacts on admissions for mental disorders. The relationship was analysed by a Negative Binomial regression model accounting for year, month, and days of week. The focus of the study was heat-wave events with periods of three or seven consecutive days above the threshold of 35oC daily maximum temperature. The preliminary study results indicated that heat-waves increased the risks for hospital admission for mental disorders (F00-79) from heat-waves of three and seven days with relative risks (RRs) of 1.16 (1.01–1.33) and 1.42 (1.02–1.99) respectively, when compared with non-heat-wave periods. Heatwave-related admissions for mental disorders increased statistically significantly among men, among residents in rural communities and in elderly. Moreover, cases for organic mental disorders including symptomatic illnesses (F0-9) and mental retardation (F70-79) raised in high risks during heat waves. The findings are novel studying a sub-tropical middle-income city, facing rapid urbanisation and epidemiological and demographic transitions.

Keywords: mental disorders, admissions for F0-9 or F70-79, maximum temperature, heat waves

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Authors: Wi Sung Yoo, Seung Woo Lee, Youn Kyoung Hur, Sung Hwan Kim

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Large-scale construction projects are continuously increasing, and the need for tools to monitor and evaluate the project success is emphasized. At the construction industry level, there are limitations in deriving performance evaluation factors that reflect the diversity of construction sites and systems that can objectively evaluate and manage performance. Additionally, there are difficulties in integrating structured and unstructured data generated at construction sites and deriving improvements. In this study, we propose the Key Performance Indicators (KPIs) to enable performance evaluation that reflects the increased diversity of construction sites and the unstructured data generated, and present a model for measuring performance by the derived indicators. The comprehensive performance of a unit construction site is assessed based on 6 areas (Time, Cost, Quality, Safety, Environment, Productivity) and 26 indicators. We collect performance indicator information from 30 construction sites that meet legal standards and have been successfully performed. And We apply data augmentation and optimization techniques into establishing measurement standards for each indicator. In other words, the KPI for construction site performance evaluation presented in this study provides standards for evaluating performance in six areas using institutional requirement data and document data. This can be expanded to establish a performance evaluation system considering the scale and type of construction project. Also, they are expected to be used as a comprehensive indicator of the construction industry and used as basic data for tracking competitiveness at the national level and establishing policies.

Keywords: key performance indicator, performance measurement, structured and unstructured data, data augmentation

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Authors: Asima Ranjan Parhi

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English language teaching-learning in higher education departments in Indian and Asian contexts needs to be one of innovation and experimentation rather than rigid prescription. The communicative language teaching has been proposing the context to be of primary importance in this process. Today, English print and electronic media have flooded the market with plenty of material suitable to the classroom context. The entries are poetic, catchy and contain a deliberate method in them which could be utilized to teach not only English language but literature, literary terms and the theory of literature. The Bollywood movies, especially through their songs have been propagating a package which may be useful to teach language and even theory in the sub-continent. While investigating, one may be fascinated to see how such material in the body of media (print and electronic), movies and popular songs generate a data for our classroom in our context, thereby developing a mass language with huge pedagogical implications. Harping on the four skills of teaching and learning of a language in general and English language in particular appears stale and mechanical in a decontextualised, matter of fact classroom. So this discussion visualizes a model beyond these skills as well as the conventional theory, literature, language classroom practices in order to build up a systematic pattern stressing the factors responsible in the particular context, that of specific language, society and culture in tune with language-literature teaching. This study intends to examine certain catchy use of the language entries in mass media which could be in the direction of inviting more such investigations in the Asian context in order to develop a common platform of decolonized pedagogy.

Keywords: pedagogy, electronic media, Bollywood, decolonized, mass media

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Authors: Rizky Kertanegara

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Reception studies is one of the cultural studies lately evolved in the realm of communication science. This qualitative study was pioneered by Stuart Hall who initiated the dominant, negotiation, and opposition of audience reading to the text of the media. In its development, this reception studies is developed by Kim Christian Schroder become multidimensional reception studies. In this update, Schroder aware that there has been a bias between readings made by the informant with readings conducted by researchers over the informant. Therefore, he classifies the reception into two dimensions, namely the dimension of reading by informants and implications dimensions conducted by researcher. Using Schroder approach, these studies seek to describe the reception of adolescent girls, as research subjects, to the elements contained sexual openness in the music video Cinta Laura as the object of research. Researcher wanted to see how they interpret the values of Western culture based on the values of their culture as a teenager. Researchers used a descriptive qualitative research method by conducting in-depth interviews to the informants who comes from a religious school. The selection of informants was done by using purposeful sampling. Collaboration with the school, the researchers were able to select informants who could provide rich data related to the topic. The analysis showed that there is permissiveness informants in addressing sexual openness in the music video. In addition, informants from Catholic schools were more open than the informant derived from Islamic schools in accepting the values of sexual openness. This permisiveness is regarded as a form of self-actualization and gender equality.

Keywords: cultural studies, multidimensional reception model, sexual openness, youth audience

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Authors: Maria Angela Bedini, Fabio Bronzini

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Most of the Italian territory is at seismic risk. Many earthquakes have hit Italy, and devastating effects have been generated. The specific objective of the research is to distinguish the negative approaches that have generated unacceptable social situations of marginalization, abandonment, and economic regression, from positive methodological approaches. On the basis of the different situations examined, the study proposes strategies and guidelines to obtain the best possible results, in Italy or abroad, in the event of new earthquakes. At national and international level, many theoretical studies address the aspects of prevention, while the comparisons, carried out in this study, between the techniques and the operative procedures applied and the results obtained are rare. The adopted methodology compares the different pre-earthquake urban-planning approaches, for the emergency (temporary urban planning), and for the post-earthquake (socio-economic-territorial processes) in Italy. Attention is placed on the current consolidated planning and programming acquisitions, pre and post-earthquake. The main results of the study concern the prospects in Italy of protection from seismic risks in the next decades. An integrated settlement system for a new economic and social model, aimed at the rebirth of territories in crisis, is proposed. Finally, the conclusions describe the disciplinary positions, procedures and the fundamental points generally shared by the scientific community for each approach, in order to identify the strategic choices and the disciplinary and management paths that will be followed in the coming decades.

Keywords: post-earthquake, seismic emergency, seismic prevention, urban planning interventions in Italy

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Authors: David Chao, John Lai, Alvin Wu, Carl Wang

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For lithium-ion batteries with multiple cell configurations, some use scenarios can cause uneven aging effects to each cell within the battery because of uneven current distribution. Hence the focus of the study is to explore the aging effect(s) on batteries with different construction designs. In order to systematically study the influence of various factors in some key battery configurations, a detailed analysis of three key battery construction factors is conducted. And those key factors are (1) terminal position; (2) cell alignment matrix; and (3) interconnect resistance between cells. In this study, the 2S2P circuitry has been set as a model multi-cell battery to set up different battery samples, and the aging behavior is studied by a cycling test to analyze the current distribution and recoverable capacity. According to the outcome of aging tests, some key findings are: (I) different cells alignment matrices can have an impact on the cycle life of the battery; (II) symmetrical structure has been identified as a critical factor that can influence the battery cycle life, and unbalanced resistance can lead to inconsistent cell aging status; (III) the terminal position has been found to contribute to the uneven current distribution, that can cause an accelerated battery aging effect; and (IV) the internal connection resistance increase can actually result in cycle life increase; however, it is noteworthy that such increase in cycle life is accompanied by a decline in battery performance. In summary, the key findings from the study can help to identify the key aging factor of multi-cell batteries, and it can be useful to effectively improve the accuracy of battery capacity predictions.

Keywords: multiple cells battery, current distribution, battery aging, cell connection

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Authors: Xiyang Li, Qi Yu, Lun Zhang

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In the face of natural disasters and other emergency situations, determining the optimal location of rescue centers is crucial for improving rescue efficiency and minimizing impact on affected populations. This paper proposes a method that integrates genetic algorithms (GA) and backpropagation neural networks (BPNN) to address the site selection optimization problem for emergency rescue centers. We utilize BPNN to accurately estimate the cost of delivering supplies from rescue centers to each temporary camp. Moreover, a genetic algorithm with a special partially matched crossover (PMX) strategy is employed to ensure that the number of temporary camps assigned to each rescue center adheres to predetermined limits. Using the population distribution data during the 2022 epidemic in Jiading District, Shanghai, as an experimental case, this paper verifies the effectiveness of the proposed method. The experimental results demonstrate that the BPNN-GA method proposed in this study outperforms existing algorithms in terms of computational efficiency and optimization performance. Especially considering the requirements for computational resources and response time in emergency situations, the proposed method shows its ability to achieve rapid convergence and optimal performance in the early and mid-stages. Future research could explore incorporating more real-world conditions and variables into the model to further improve its accuracy and applicability.

Keywords: emergency rescue centers, genetic algorithms, back-propagation neural networks, site selection optimization

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Authors: Divya Vats, Sanjay Mahajani

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The clarification of sugarcane juice plays a pivotal role in the production of non-centrifugal sugar (NCS), profoundly influencing the quality of the final NCS product. In this study, we have investigated the kinetics and mathematical modeling of the batch clarification process. The turbidity of the clarified cane juice (NTU) emerges as the determinant of the end product’s color. Moreover, this parameter underscores the significance of considering other variables as performance indicators for accessing the efficacy of the clarification process. Temperature-controlled experiments were meticulously conducted in a laboratory-scale batch mode. The primary objective was to discern the essential and optimized parameters crucial for augmenting the clarity of cane juice. Additionally, we explored the impact of pH and flocculant loading on the kinetics. Particle Image Velocimetry (PIV) is employed to comprehend the particle-particle and fluid-particle interaction. This technique facilitated a comprehensive understanding, paving the way for the subsequent multiphase computational fluid dynamics (CFD) simulations using the Eulerian-Lagrangian approach in the Ansys fluent. Impressively, these simulations accurately replicated comparable velocity profiles. The final mechanism of this study helps to make a mathematical model and presents a valuable framework for transitioning from the traditional batch process to a continuous process. The ultimate aim is to attain heightened productivity and unwavering consistency in product quality.

Keywords: non-centrifugal sugar, particle image velocimetry, computational fluid dynamics, mathematical modeling, turbidity

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Authors: Fabiola Trejo Perez, Rolando Diaz Loving

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Sexual pleasure consists of the positively valued feelings induced by sexual stimuli, but it is also weighed down by pop-psychological baggage, and subjected to cross-cultural and cross-historical variation. Social and individual interpretations of what can or can’t be considered as pleasurable are intertwined with culture’s predominant values, norms and beliefs. For each culture, sexual norms work as a guide to be followed in order to model socially accepted behaviors. Therefore, cultural messages regarding sexuality are usually directed to restrict men and women from enjoyment, sexual satisfaction and specifically orgasm. Given that sexual pleasure hasn’t been recognized as an accepted topic of open discussion, particularly for women, people have to eventually complement their knowledge using their own experience filling in the blanks from what little has been said. Thus, this research aims to identify which are the particular social messages associated with the easing or inhibition of sexual pleasure. Three hundred Mexican men and women ages 25 to 35 years old answered a self-report survey composed by the Inventory of facilitators and inhibitors of sexual pleasure and the Sexual premises questionnaire via pencil-paper and online. Results show a high endorsement to double standard messages associated with higher levels of sexual pleasure inhibitors like feeling pressured to have sexual activity, guilt and inability to reach orgasm, in contrast with people who endorse more permissive norms and beliefs, feeling connected to their sexual partners and confident with themselves. These results illustrate that the shaping of sexuality, from experience to society, is comprised of an important relationship between culture and sexual pleasure.

Keywords: culture, sexual double standard, sexual norms and beliefs, sexual pleasure

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Authors: Zhiyong Li, Hiroshi Katayama

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Since 1990s, e-commerce and internet business have been grown gradually over the word and customers tend to express their demand attributes in terms of specification requirement on parts, component, product structure etc. This paper deals with designing effective decoupling points for build to order systems under e-commerce environment, which can be realized through tradeoff relation analysis between two major criteria, customer order lead time and value of work in progress. These KPIs are critical for successful BTO business, namely time-based service effectiveness on coping with customer requirements for the first issue and cost effective ness with risk aversive operations for the second issue. Approach of this paper consists of investigation of successful business standing for BTO scheme, manufacturing model development of this scheme, quantitative evaluation of proposed models by calculation of two KPI values under various decoupling point distributions and discussion of the results brought by pattern of decoupling point distribution, where some cases provide the pareto optimum performances. To extract the relevant trade-off relation between considered KPIs among 2-dimensional resultant performance, useful logic developed by former research work, i.e. Katayama and Fonseca, is applied. Obtained characteristics are evaluated as effective information for managing BTO manufacturing businesses.

Keywords: build-to-order (BTO), decoupling point, e-commerce, order-to-delivery lead time (ODLT), work in progress (WIP)

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Authors: Birhanu Betela Warssamo

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Background: There is limited evidence on the prevalence and risk factors for hepatitis C virus (HCV) infection among waste handlers in the Sidama region, Ethiopia; however, this knowledge is necessary for the effective prevention of HCV infection in the region. Methods: A cross-sectional study was conducted among randomly selected waste collectors from October 2021 to 30 July 2022 in different public hospitals in the Sidama region of Ethiopia. Serum samples were collected from participants and screened for anti-HCV using a rapid immunochromatography assay. Socio-demographic and risk factor information of waste handlers was gathered by pretested and well-structured questionnaires. The generalized linear model (GLM) was conducted using R software, and P-value < 0.05 was declared statistically significant. Results: From a total of 282 participating waste handlers, 16 (5.7%) (95% CI, 4.2 – 8.7) were infected with the hepatitis C virus. The educational status of waste handlers was the significant demographic variable that was associated with the hepatitis C virus (AOR = 0.055; 95% CI = 0.012 – 0.248; P = 0.000). More married waste handlers, 12 (75%), were HCV positive than unmarried, 4 (25%) and married waste handlers were 2.051 times (OR = 2.051, 95%CI = 0.644 –6.527, P = 0.295) more prone to HCV infection, compared to unmarried, which was statistically insignificant. The GLM showed that exposure to blood (OR = 8.26; 95% CI = 1.878–10.925; P = 0.037), multiple sexual partners (AOR = 3.63; 95% CI = 2.751–5.808; P = 0.001), sharp injury (AOR = 2.77; 95% CI = 2.327–3.173; P = 0.036), not using PPE (AOR = 0.77; 95% CI = 0.032–0.937; P = 0.001), contact with jaundiced patient (AOR = 3.65; 95% CI = 1.093–4.368; P = 0 .0048) and unprotected sex (AOR = 11.91; 95% CI = 5.847–16.854; P = 0.001) remained statistically significantly associated with HCV positivity. Conclusions: The study revealed that there was a high prevalence of hepatitis C virus infection among waste handlers in the Sidama region, Ethiopia. This demonstrated that there is an urgent need to increase preventative efforts and strategic policy orientations to control the spread of the hepatitis C virus.

Keywords: Hepatitis C virus, risk factors, waste handlers, prevalence, Sidama Ethiopia

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Authors: Mia I. Allen, Bernard N. Johnson, Gagan Deep, Yixin Su, Sangeeta Singth, Ashish Kumar, , Michael A. Nader

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With no FDA-approved treatments for cocaine use disorders (CUD), research has focused on the behavioral and neuropharmacological effects of cocaine in animal models, with the goal of identifying novel interventions. While the majority of people with CUD also use tobacco/nicotine, the majority of preclinical cocaine research does not include the co-use of nicotine. The present study examined nicotine and cocaine co-use under several conditions of intravenous drug self-administration in monkeys. In Experiment 1, male rhesus monkeys (N=3) self-administered cocaine (0.001-0.1 mg/kg/injection) alone and cocaine+nicotine (0.01-0.03 mg/kg/injection) under a progressive-ratio schedule of reinforcement. When nicotine was added to cocaine, there was a significant leftward shift and significant increase in peak break point. In Experiment 2, socially housed female and male cynomolgus monkeys (N=14) self-administered cocaine under a concurrent drug-vs-food choice schedule. Combining nicotine significantly decreased cocaine choice ED50 values (i.e., shifted the cocaine dose-response curve to the left) in females but not in males. There was no evidence of social rank differences. In delay discounting studies, the co-use of nicotine and cocaine required significantly larger delays to the preferred drug reinforcer to reallocate choice compared with cocaine alone. Overall, these results suggest drug interactions of nicotine and cocaine co-use is not simply a function of potency but rather a fundamentally distinctive condition that should be utilized to better understand the neuropharmacology of CUD and the evaluation of potential treatments.

Keywords: polydrug use, animal models, nonhuman primates, behavioral pharmacology, drug self-administration

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Authors: Jiashu Shen

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Objectives: Spirometry is a basic reference for health evaluation which is widely used in clinical. Previous reference of spirometry is not applicable because of drastic changes of social and natural circumstance in China. A new reference values for the spirometry of the Chinese population is extremely needed. Method: Spirometric reference value was established using the statistical modeling method Generalized Additive Models for Location, Scale and Shape for forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, and maximal mid-expiratory flow (MMEF). Results: Data from 236,606 healthy non-smokers aged 4–90 years was collected from the MJ Health Check database. Spirometry equations for FEV1, FVC, MMEF, and FEV1/FVC were established, including the predicted values and lower limits of normal (LLNs) by sex. The predictive equations that were developed for the spirometric results elaborated the relationship between spirometry and age, and they eliminated the effects of height as a variable. Most previous predictive equations for Chinese spirometry were significantly overestimated (to be exact, with mean differences of 22.21% in FEV1 and 31.39% in FVC for males, along with differences of 26.93% in FEV1 and 35.76% in FVC for females) or underestimated (with mean differences of -5.81% in MMEF and -14.56% in FEV1/FVC for males, along with a difference of -14.54% in FEV1/FVC for females) the results of lung function measurements as found in this study. Through cross-validation, our equations were established as having good fit, and the means of the measured value and the estimated value were compared, with good results. Conclusions: Our study updates the spirometric reference equations for Chinese people of all ages and provides comprehensive values for both physical examination and clinical diagnosis.

Keywords: Chinese, GAMLSS model, reference values, spirometry

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Authors: Alireza Rasekh, Peter Sergeant, Jan Vierendeels

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This paper copes with the numerical simulation for convective heat transfer in the stator disk of an axial flux permanent magnet (AFPM) electrical machine. Overheating is one of the main issues in the design of AFMPs, which mainly occurs in the stator disk, so that it needs to be prevented. A rotor-stator configuration with 16 magnets at the periphery of the rotor is considered. Air is allowed to flow through openings in the rotor disk and channels being formed between the magnets and in the gap region between the magnets and the stator surface. The rotating channels between the magnets act as a driving force for the air flow. The significant non-dimensional parameters are the rotational Reynolds number, the gap size ratio, the magnet thickness ratio, and the magnet angle ratio. The goal is to find correlations for the Nusselt number on the stator disk according to these non-dimensional numbers. Therefore, CFD simulations have been performed with the multiple reference frame (MRF) technique to model the rotary motion of the rotor and the flow around and inside the machine. A minimization method is introduced by a pattern-search algorithm to find the appropriate values of the reference temperature. It is found that the correlations are fast, robust and is capable of predicting the stator heat transfer with a good accuracy. The results reveal that the magnet angle ratio diminishes the stator heat transfer, whereas the rotational Reynolds number and the magnet thickness ratio improve the convective heat transfer. On the other hand, there a certain gap size ratio at which the stator heat transfer reaches a maximum.

Keywords: AFPM, CFD, magnet parameters, stator heat transfer

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Ahmed H. Elkholy

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An elastic analysis is developed to obtain the distribution of stresses, strains, bending moment and deformation for a thin hollow, variable thickness cylindrical specimen when subjected to different biaxial loadings. The specimen was subjected to a combination of internal pressure, axial tensile loading and external pressure. Several axial to circumferential stress ratios were investigated in detail. The analytical model was then validated using experimental results obtained from a test rig using several biaxial loadings. Based on the preliminary results obtained, the specimen was then modified geometrically to ensure uniform strain distribution through its wall thickness and along its gauge length. The new design of the specimen has a higher buckling strength and a maximum value of equivalent stress according to the maximum distortion energy theory. A cyclic function generator of the standard servo-controlled, electro-hydraulic testing machine is used to generate a specific signal shape (sine, square,…) at a certain frequency. The two independent controllers of the electronic circuit cause an independent movement to each servo-valve piston. The movement of each piston pressurizes the upper and lower sides of the actuators alternately. So, the specimen will be subjected to axial and diametral loads independent of each other. The hydraulic system has two different pressures: one pressure will be responsible for axial stress produced in the specimen and the other will be responsible for the tangential stress. Changing the two pressure ratios will change the stress ratios accordingly. The only restriction on the maximum stress obtained is the capacity of the testing system and specimen instability due to buckling.

Keywords: biaxial, fatigue, stress, testing

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Authors: Jiandong Ren, Lijun Zhao, Peng Chen

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Nafamostat (NA), a synthetic broad-spectrum serine protease inhibitor, has been routinely employed for the treatment of acute pancreatitis (AP) and other inflammatory-associated diseases in some East Asia countries. Although the potent inhibitory activity against inflammation-related proteases such as thrombin, trypsin, kallikrein, plasmin, coagulation factors and complement factors is generally considered to be responsible for the anti-inflammatory effects of NA, precise target and molecular mechanism underlying the anti-inflammatory activity in the treatment of AP remain largely unknown yet. As an intracellular inflammatory signaling platform, the NOD-like receptor protein 3 (NLRP3) inflammasome is recently identified to be involved in the development of AP. In present study, we have revealed that NA alleviated pancreatic injury in a caerulein-induced AP model by inhibiting the NLRP3 inflammasome activation in pancreas. Mechanistically, NA interacted with HDAC6, a cytoplasmic deacetylase implicated in the NLRP3 inflammasome pathway, and efficiently abrogated the function of HDAC6. This property enabled NA to influence HDAC6 dependent NF-κB transcriptional activity and thus block NF-κB-driven transcriptional priming of NLRP3 inflammasome. Moreover, NA exerted the potential to interfere HDAC6-mediated intracellular transport of NLRP3, thereby leading to the failure of NLRP3 inflammasome activation. Our current work has provided valuable insight into the molecular mechanism underlying the immunomodulatory effect of NA in treatment of AP, highlighting its promising application in prevention of NLRP3 inflammasome-associated inflammatory pathological damage.

Keywords: acute pancreatitis, HDAC6, nafamostat, NLRP3 inflammasome

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Authors: Yu-ding Du, Qi-lian Bao, Nassim Bessaad, Lin Liu

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The Global Navigation Satellite System (GNSS) is regarded as an effective approach for the purpose of replacing the large amount used track-side balises in modern train localization systems. This paper describes a method based on the data fusion of a GNSS receiver sensor and an odometer sensor that can significantly improve the positioning accuracy. A digital track map is needed as another sensor to project two-dimensional GNSS position to one-dimensional along-track distance due to the fact that the train’s position can only be constrained on the track. A model trained by BP neural network is used to estimate the trend positioning error which is related to the specific location and proximate processing of the digital track map. Considering that in some conditions the satellite signal failure will lead to the increase of GNSS positioning error, a detection step for GNSS signal is applied. An adaptive weighted fusion algorithm is presented to reduce the standard deviation of train speed measurement. Finally an Extended Kalman Filter (EKF) is used for the fusion of the projected 1-D GNSS positioning data and the 1-D train speed data to get the estimate position. Experimental results suggest that the proposed method performs well, which can reduce positioning error notably.

Keywords: multi-sensor data fusion, train positioning, GNSS, odometer, digital track map, map matching, BP neural network, adaptive weighted fusion, Kalman filter

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Authors: Seyed M. Khatami, H. Naderpour, R. Vahdani, R. C. Barros

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Many previous studies have been carried out to calculate the impact force and the dissipated energy between two neighboring buildings during seismic excitation, when they collide with each other. Numerical studies are an important part of impact, which several researchers have tried to simulate the impact by using different formulas. Estimation of the impact force and the dissipated energy depends significantly on some parameters of impact. Mass of bodies, stiffness of spring, coefficient of restitution, damping ratio of dashpot and impact velocity are some known and unknown parameters to simulate the impact and measure dissipated energy during collision. Collision is usually shown by force-displacement hysteresis curve. The enclosed area of the hysteresis loop explains the dissipated energy during impact. In this paper, the effect of using different types of impact models is investigated in order to calculate the impact force. To increase the accuracy of impact model and to optimize the results of simulations, a new damping equation is assumed and is validated to get the best results of impact force and dissipated energy, which can show the accuracy of suggested equation of motion in comparison with other formulas. This relation is called "n-m". Based on mathematical relation, an initial value is selected for the mentioned coefficients and kinetic energy loss is calculated. After each simulation, kinetic energy loss and energy dissipation are compared with each other. If they are equal, selected parameters are true and, if not, the constant of parameters are modified and a new analysis is performed. Finally, two unknown parameters are suggested to estimate the impact force and calculate the dissipated energy.

Keywords: impact force, dissipated energy, kinetic energy loss, damping relation

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Authors: Muhammad Faizan Chinannai, Jaeseung Lee, Mohamed Hassan Gundu, Hyunchul Ju

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Fuel cell is known to be an effective renewable energy resource which is commercializing in the present era. It is really important to know about the improvement in performance even when the system faces some defects. This study was carried out to analyze the performance of the Polymer electrolyte fuel cell (PEFCs) under different operating conditions such as current density, relative humidity and Pt loadings considering defects with load changes. The purpose of this study is to analyze the response of the fuel cell system with defects in Balance of Plants (BOPs) and catalyst layer (CL) degradation by maintaining the coolant flow rate as such to preserve the cell temperature at the required level. Multi-Scale Simulation of 3D two-phase PEFC model with coolant was carried out under different load conditions. For detailed analysis and performance comparison, extensive contours of temperature, current density, water content, and relative humidity are provided. The simulation results of the different cases are compared with the reference data. Hence the response of the fuel cell stack with defects in BOP and CL degradations can be analyzed by the temperature difference between the coolant outlet and membrane electrode assembly. The results showed that the Failure of the humidifier increases High-Frequency Resistance (HFR), air flow defects and CL degradation results in the non-uniformity of current density distribution and high cathode activation overpotential, respectively.

Keywords: PEM fuel cell, fuel cell modeling, performance analysis, BOP components, current density distribution, degradation

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Authors: Abhimanyu Pati, Prabir K. Bandyopadhyay

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The paper intends to highlight the significance of Digital Manufacturing (DM) strategy in support and achievement of business strategy and goals of any manufacturing organization. Towards this end, DM initiatives have been given a process perspective, while not undermining its technological significance, with a view to link its benefits directly with fulfilment of customer needs and expectations in a responsive and cost-effective manner. A digital process model has been proposed to categorize digitally enabled organizational processes with a view to create synergistic groups, which adopt and use digital tools having similar characteristics and functionalities. This will throw future opportunities for researchers and developers to create a unified technology environment for integration and orchestration of processes. Secondly, an effort has been made to apply “what” and “how” features of Quality Function Deployment (QFD) framework to establish the relationship between customers’ needs – both for external and internal customers, and the features of various digital processes, which support for the achievement of these customer expectations. The paper finally concludes that in the present highly competitive environment, business organizations cannot thrive to sustain unless they understand the significance of digital strategy and integrate it with their business strategy with a clearly defined implementation roadmap. A process-oriented approach to DM strategy will help business executives and leaders to appreciate its value propositions and its direct link to organization’s competitiveness.

Keywords: knowledge management, cloud computing, knowledge management approaches, cloud-based knowledge management

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Authors: Adele Pierre, Nadia Amoroso

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Changing climate patterns are resulting in increased in storm severity, challenging traditional methods of managing stormwater runoff. This research compares a system of bioswales to existing curb and gutter infrastructure in a post-industrial streetscape of Hamilton, Ontario. Using the geodesign process, including rule-based set parameters and an integrated approach combining geospatial information with stakeholder input, a section of Ottawa St. North was modelled to show how green infrastructure can ease the burden on aging, combined sewer systems. Qualitative data was gathered from residents of the neighbourhood through field notes, and quantitative geospatial data through GIS and site analysis. Parametric modelling was used to generate multiple design scenarios, each visualizing resulting impacts on stormwater runoff along with their calculations. The selected design scenarios offered both an aesthetically pleasing urban bioswale street-scape system while minimizing and controlling stormwater runoff. Interactive maps, videos and the 3D model were presented for stakeholder comment via ESRI’s (Environmental System Research Institute) web-scene. The results of the study demonstrate powerful tools that can assist landscape architects in designing, collaborating and communicating stormwater strategies.

Keywords: bioswale, geodesign, data-driven and rule-based design, geodesign, GIS, stormwater management

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Authors: Antoine Vikkey Hinson, Menonli Adjobimey, Gemayel Ahmed Biokou, Rose Mikponhoue

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Introduction: Construction industry is a critical concern with regard to Health and Safety Service worldwide. World health Organization revealed that work-related disease and trauma were held responsible for the death of one million nine hundred thousand people in 2016. The aim of this study it was to determine the prevalence and factors associated with the occurrence of work accidents in a construction industry in Benin. Method: It was a descriptive cross-sectional and analytical study. Data analysis was performed with R software 4.1.1. In multivariate analysis, we performed a binary logistic regression. OR adjusted (ORa) association measures and their 95% confidence interval [CI95%] were presented for the explanatory variables used in the final model. The significance threshold for all tests selected was 5% (p < 0.05) Result: In this study, 472 workers were included, and, of these, 452 (95.7%) were men corresponding to a sex ratio of 22.6. The average age of the workers was 33 years ± 8.8 years. Workers were mostly laborers (84.7%), and had declared having inadequate personal protective equipment (50.6%, n=239). The prevalence of work accidents is 50.8%. Collision with a rolling stock (25.8%), cut (16.2%), and stumbling (16.2%) were the main types of work accidents on the construction site. Four factors were associated with contributing to work accidents. Fatigue or exhaustion (ORa : 1.53[1.03 ; 2.28]); The use of dangerous tools (ORa : 1.81 [1.22 ; 2.71]); The various laborers’ jobs (ORa : 4.78 [2.62 ; 9.21]); and seniority in the company ≥ 4 years (ORa : 2.00 [1.35 ; 2.96]). Conclusion: This study allowed us to identify the associated factors. It is imperative to implement a rigorous policy of occupational health and security mostly the continuing training for workers safe, the supply of appropriate work tools and protective

Keywords: prevalence, work accident, associated factors, construction, benin

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Authors: Wanessa G. Oliveira, Fernando C. Capovilla

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Capovilla and Raphael’s Libras Dictionary documents a corpus of 4,200 Brazilian Sign Language (Libras) signs. Duduchi and Capovilla’s software SignTracking permits users to retrieve signs even when ignoring the gloss corresponding to it and to discover the meaning of all 4,200 signs sign simply by clicking on graphic menus of the sign characteristics (phonemes). Duduchi and Capovilla have discovered that the ease with which any given sign can be retrieved is an inverse function of the average popularity of its component phonemes. Thus, signs composed of rare (distinct) phonemes are easier to retrieve than are those composed of common phonemes. SignTracking offers a means of computing the average popularity of the phonemes that make up each one of 4,200 signs. It provides a precise measure of the degree of ease with which signs can be retrieved, and sign meanings can be discovered. Duduchi and Capovilla’s logarithmic model proved valid: The degree with which any given sign can be retrieved is an inverse function of the arithmetic mean of the logarithm of the popularity of each component phoneme. Capovilla, Raphael and Mauricio’s New Libras Dictionary documents a corpus of 10,400 Libras signs. The present analysis revealed Libras DNA structure by mapping the incidence of 501 sign phonemes resulting from the layered distribution of five parameters: 163 handshape phonemes (CherEmes-ManusIculi); 34 finger shape phonemes (DactilEmes-DigitumIculi); 55 hand placement phonemes (ArtrotoToposEmes-ArticulatiLocusIculi); 173 movement dimension phonemes (CinesEmes-MotusIculi) pertaining to direction, frequency, and type; and 76 Facial Expression phonemes (MascarEmes-PersonalIculi).

Keywords: Brazilian sign language, lexical retrieval, libras sign, sign phonology

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Authors: Andres Piña, Amy Meléndez, Pablo Cano, Tomas Cahuich

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The purpose of this project is to propose a quick and environmentally friendly alternative to measure the quality of oils used in food industry. There is evidence that repeated and indiscriminate use of oils in food processing cause physicochemical changes with formation of potentially toxic compounds that can affect the health of consumers and cause organoleptic changes. In order to assess the quality of oils, non-destructive optical techniques such as Interferometry offer a rapid alternative to the use of reagents, using only the interaction of light on the oil. Through this project, we used interferograms of samples of oil placed under different heating conditions to establish the changes in their quality. These interferograms were obtained by means of a Mach-Zehnder Interferometer using a beam of light from a HeNe laser of 10mW at 632.8nm. Each interferogram was captured, analyzed and measured full width at half-maximum (FWHM) using the software from Amcap and ImageJ. The total of FWHMs was organized in three groups. It was observed that the average obtained from each of the FWHMs of group A shows a behavior that is almost linear, therefore it is probable that the exposure time is not relevant when the oil is kept under constant temperature. Group B exhibits a slight exponential model when temperature raises between 373 K and 393 K. Results of the t-Student show a probability of 95% (0.05) of the existence of variation in the molecular composition of both samples. Furthermore, we found a correlation between the Iodine Indexes (Physicochemical Analysis) and the Interferograms (Optical Analysis) of group C. Based on these results, this project highlights the importance of the quality of the oils used in food industry and shows how Interferometry can be a useful tool for this purpose.

Keywords: food industry, interferometric, oils, quality control

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Authors: Michael C. Barbecho, Romeo B. Morcilla

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This study focused on the development of a solar powered front wheel drive electric trike for personal use and short distance travel, utilizing solar power and a variable speed transmission to adapt in places where varying road grades and unavailability of plug-in charging stations are of great problems. The actual performance of the vehicle was measured in terms of duration of charging using solar power, distance travel and battery power duration, top speed developed at full power, and load capacity. This project followed the research and development process which involved planning, designing, construction, and testing. Solar charging tests revealed that the vehicle requires 6 to 8 hours sunlight exposure to fully charge the batteries. At full charge, the vehicle can travel 35 km utilizing battery power down to 42%. Vehicle showed top speed of 25 kph at 0 to 3% road grade carrying a maximum load of 122 kg. The maximum climbing grade was 23% with the vehicle carrying a maximum load of 122 kg. Technically the project was feasible and can be a potential model for possible conversion of traditional Philippine made “pedicabs” and gasoline engine powered tricycle into modern electric vehicles. Moreover, it has several technical features and advantages over a commercialized electric vehicle such as the use solar charging system and variable speed power transmission and front drive power train for adaptability in any road gradient.

Keywords: electric vehicle, solar vehicles, front drive, solar, solar power

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Authors: Habtamu Anagaw Muluneh, Gebregziabher Kahsay, Tamiru Negussie

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Theoretical study of the density of state, condensation energy, specific heat, and magnetization in a spin-triplet superconductor are the main goals of this work. Utilizing the retarded double-time temperature-dependent Green's function formalism and building a model Hamiltonian for the system at hand, we were able to derive the expressions for the parameters mentioned above. The phase diagrams are plotted using MATLAB scripts. From the phase diagrams, the density of electrons increases as the excitation energy increases, and the maximum excitation energy is equal to the superconducting gap, but it decreases when the value exceeds the gap and finally becomes the same as the density of the normal state. On the other hand, the condensation energy decreases with the increase in temperature and attains its minimum value at the superconducting transition temperature but increases with the increase in superconducting transition temperature (TC) and finally becomes zero, implying the superconducting energy is equal to the normal state energy. The specific heat increases with the increase in temperature, attaining its maximum value at the TC and then undergoing a jump, showing the presence of a second-order phase transition from the superconducting state to the normal state. Finally, the magnetization of both the itinerant and localized electrons decreases with the increase in temperature and finally becomes zero at TC = 1.6 K and magnetic phase transition temperature T = 2 K, respectively, which results in a magnetic phase transition from a ferromagnetic to a paramagnetic state. Our finding is in good agreement with the previous findings.

Keywords: spin triplet superconductivity, Green’s function, condensation energy, density of state, specific heat, magnetization

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Authors: Ahmed Boufedah Badissi, Ahmed Beroual, Farid Boursas

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This research aims to elucidate the role of coarse aggregate in influencing the fresh properties of normal-strength concrete. Specifically, it is aimed to identify the optimal gradation of coarse aggregate to enhance workability. While existing literature discusses the impact of aggregate granularity on concrete workability, more numerical data or models need to quantify the relationship between workability, granularity, and coarse aggregate shape. The main objective is to create a model that describes how coarse aggregate morphology contributes to fresh concrete properties. To investigate the effect of coarse aggregate gradation on Normal Strength Concrete (NSC) workability, various combinations of coarse aggregates (4/22.4 mm) were produced in the laboratory, utilizing three elementary classes: finer coarse aggregate 4/8 mm (Fca), medium coarse aggregate 8/16 mm (Mca), and coarser coarse aggregate 16/22.4 mm (Cca). We introduced a factor, FCR (Finer to Coarser coarse aggregate Ratio), as a numerical parameter to provide a quantitative evaluation and more detailed results analysis. Quantitative characterization parameters for coarse aggregate morphology were established, exploring the influence of particle size distribution, specific surface, and aggregate shape on workability. The research findings are significant for establishing correlations between coarse aggregate morphology and concrete properties. FCR emerges as a valuable tool for predicting the impact of aggregate gradation variations on concrete. The results of this study create a valuable database for construction professionals and concrete producers, affirming that the fresh properties of NSC are intricately linked to coarse aggregate morphology, particularly gradation.

Keywords: morphology, coarse aggregate, workability, fresh properties, gradation

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Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

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Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

Procedia PDF Downloads 87