Search results for: time domain analysis

Authors: Khosro Barkhordari, Fateme Sadr, Mina Pashang

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Back ground: Blood transfusion is one of the major issues in cardiac surgery patients. Transfusing patients based on fixed cut-off points of hemoglobin is the current protocol in most institutions. The hemoglobin level of 7- 10 has been suggested for blood transfusion in cardiac surgery patients. We aimed to evaluate if blood transfusion based on change in percentage of hematocrit has different outcomes. Methods: In this retrospective cohort study, we investigated the early postoperative outcome of cardiac surgery patients who received blood transfusions at Tehran Heart Center Hospital, IRAN. We reviewed and analyzed the basic characteristics and clinical data of 700 patients who met our exclusion and inclusion criteria. The two groups of blood transfused patients were compared, those who have 30-50 percent decrease in basal hematocrit versus those with 10 -29 percent decrease. Results: This is ongoing study, and the results would be completed in two weeks after analysis of the date. Conclusion: Early analysis has shown no difference in early post-operative outcomes between the two groups, but final analysis will be completed in two weeks. 1-Department of Anesthesiology and Critical Care, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, IRAN 2- Department of Research, Tehran Heart Center, Tehran, IRAN Quantitative variables were compared using the Student t-test or the Mann‐Whitney U test, as appropriate, while categorical variables were compared using the χ2 or the Fisher exact test, as required. Our intention was to compare the early postoperative outcomes between the two groups, which include 30 days mortality, Length of ICU stay, Length of hospital stay, Intubation time, Infection rate, acute kidney injury, and respiratory complications. The main goal was to find if transfusing blood based on changes in hematocrit from a basal level was better than to fixed cut-off point regarding early post-operative outcomes. This has not been studied enough and may need randomized control trials.

Keywords: post-operative, cardiac surgery, outcomes, blood transfusion

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Authors: Swathi M. Vanniarajan

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Reading research suggests that online contextual vocabulary comprehension while reading is an interactive and integrative process. One’s success in it depends on a variety of factors including the amount and the nature of available linguistic and nonlinguistic cues, his/her analytical and integrative skills, schema memory (content familiarity), and processing speed characterized along the continuum of controlled to automatic processing. The experiment reported here, conducted with 30 native speakers as one group and 30 nonnative speakers as another group (all graduate students), hypothesized that while working on (24) tasks which required them to comprehend an unfamiliar word in real time without backtracking, due to the differences in the nature of their respective reading processes, the nonnative subjects would be less able to construct the meanings of the unknown words by integrating the multiple but sufficient contextual cues provided in the text but the native subjects would be able to. The results indicated that there were significant inter-group as well as intra-group differences in terms of the quality of definitions given. However, when given additional time, while the nonnative speakers could significantly improve the quality of their definitions, the native speakers in general would not, suggesting that all things being equal, time is a significant factor for success in nonnative vocabulary and reading comprehension processes and that accuracy precedes automaticity in the development of nonnative reading processes also.

Keywords: reading, second language processing, vocabulary comprehension

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Authors: Bina Kumari, Subir K. Sarkar, Pradipta Bandyopadhyay

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The autocorrelation function of the density fluctuation is studied in each of the two phases in a Gibbs Ensemble Monte Carlo (GEMC) simulation of the problem of phase separation for a square well potential with various values of its range. We find that the normalized autocorrelation function is described very well as a linear combination of an exponential function with a time scale τ₂ and a stretched exponential function with a time scale τ₁ and an exponent α. Dependence of (α, τ₁, τ₂) on the parameters of the GEMC algorithm and the range of the square well potential is investigated and interpreted. We also analyse the issue of how to choose the parameters of the GEMC simulation optimally.

Keywords: autocorrelation function, density fluctuation, GEMC, simulation

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Authors: I. Benhsine, M. Hellou, F. Lominé, Y. Roques

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During the manufacture of fertilizer, it is necessary to add water for granulation purposes. The water content is then removed or reduced using rotary dryers. They are commonly used to dry wet granular materials and they are usually fitted with lifting flights. The transport of granular materials occurs when particles cascade from the lifting flights and fall into the air stream. Each cascade consists of a lifting and a falling cycle. Lifting flights are thus of great importance for the transport of granular materials along the dryer. They also enhance the contact between solid particles and the air stream. Optimization of the drying process needs an understanding of the behavior of granular materials inside a rotary dryer. Different approaches exist to study the movement of granular materials inside the dryer. Most common of them are based on empirical formulations or on study the movement of the bulk material. In the present work, we are interested in the behavior of each particle in the cross section of the dryer using Discrete Element Method (DEM) to understand. In this paper, we focus on studying the hold-up, the cascade patterns, the falling time and the falling length of the particles leaving the flights. We will be using two segment flights. Three different profiles are used: a straight flight (180° between both segments), an angled flight (with an angle of 150°), and a right-angled flight (90°). The profile of the flight affects significantly the movement of the particles in the dryer. Changing the flight angle changes the flight capacity which leads to different discharging profile of the flight, thus affecting the hold-up in the flight. When the angle of the flight is reduced, the range of the discharge angle increases leading to a more uniformed cascade pattern in time. The falling length and the falling time of the particles also increase up to a maximum value then they start decreasing. Moreover, the results show an increase in the falling length and the falling time up to 70% and 50%, respectively, when using a right-angled flight instead of a straight one.

Keywords: discrete element method, granular materials, lifting flight, rotary dryer

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Authors: U. Waqas, M. F. Ahmed, A. Mehmood, M. A. Rashid

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In geophysical exploration surveys, the quality of acquired data holds significant importance before executing the data processing and interpretation phases. In this study, 2D seismic reflection survey data of Fort Abbas area, Cholistan Desert, Pakistan was taken as test case in order to assess its quality on statistical bases by using normalized root mean square error (NRMSE), Cronbach’s alpha test (α) and null hypothesis tests (t-test and F-test). The analysis challenged the quality of the acquired data and highlighted the significant errors in the acquired database. It is proven that the study area is plain, tectonically least affected and rich in oil and gas reserves. However, subsurface 3D modeling and contouring by using acquired database revealed high degrees of structural complexities and intense folding. The NRMSE had highest percentage of residuals between the estimated and predicted cases. The outcomes of hypothesis testing also proved the biasness and erraticness of the acquired database. Low estimated value of alpha (α) in Cronbach’s alpha test confirmed poor reliability of acquired database. A very low quality of acquired database needs excessive static correction or in some cases, reacquisition of data is also suggested which is most of the time not feasible on economic grounds. The outcomes of this study could be used to assess the quality of large databases and to further utilize as a guideline to establish database quality assessment models to make much more informed decisions in hydrocarbon exploration field.

Keywords: Data quality, Null hypothesis, Seismic lines, Seismic reflection survey

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Authors: Baishali Deb, Hari Om Pandey, Shrilla Elangbam, Mukesh Singh, Ayon Tarafdar, A. K. S. Tomar, A. K. Pandey, Triveni Dutt

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The goal of the present investigation was to determine the impact of social stress on behavioural characteristics, physiological responses, and haemato-biochemical indicators under various social environments in Tharparkar cattle. Serum cortisol and faecal cortisol metabolites analysis were used to determine the stress level of Tharparkar cattle. Social isolation and social mixing were the two different social circumstances used to evaluate the animals. In both the experiments i.e., social isolation and social mixing, the lying period of animals decreased significantly (p<0.05) while standing period significantly (p<0.05) increased. Frequency and duration of activities like idling, walking, exploration, oral manipulation, and elimination increased significantly (p<0.05) in Tharparkar cattle after being subjected to social isolation and social mixing. Time spent in grooming (self-grooming and allo-grooming) in respect to social isolation significantly increased during isolation and post-reunion, whereas there was a significant (p<0.05) decline in the grooming behaviour especially allo-grooming during mixing of the animals. Feeding and rumination time also decreased significantly (p<0.05) in animals during both the experiments. Physiological parameters such as respiration rate, heart rate and pulse rate increased during the treatment periods. There was no significant difference in the haematological parameters for both the experiments. There was significant (p<0.05) increase in serum cortisol and faecal cortisol metabolites (FCM) concentration in animals subjected to social stress. Therefore, it can be concluded that social stress strongly impacts the behaviour and physiological parameters of the animals, causing stress and nervousness, proving that social stress is a valid psychological stress in animals. The higher concentration of FCM in Tharparkar cattle subjected to social stress, further supported by higher serum cortisol and behaviour manifestations, suggest that FCM could be used to assess stress response as a non-invasive method.

Keywords: social stress, fecal cortisol metabolites, non-invasive, animal welfare, behaviour

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Authors: Sherly M. A., Varsha Vijaykumar, Subhankar Karmakar, Terence Chan, Christian Rau

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This study aims at proposing an indicator-based framework for assessing social vulnerability of any coastal megacity to floods. The final set of indicators of social vulnerability are chosen from a set of feasible and available indicators which are prepared using a Geographic Information System (GIS) framework on a smaller scale considering 1-km grid cell to provide an insight into the spatial variability of vulnerability. The optimal weight for each individual indicator is assigned using data envelopment analysis (DEA) as it avoids subjective weights and improves the confidence on the results obtained. In order to de-correlate and reduce the dimension of multivariate data, principal component analysis (PCA) has been applied. The proposed methodology is demonstrated on twenty four wards of Mumbai under the jurisdiction of Municipal Corporation of Greater Mumbai (MCGM). This framework of vulnerability assessment is not limited to the present study area, and may be applied to other urban damage centers.

Keywords: urban floods, vulnerability, data envelopment analysis, principal component analysis

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Authors: Michele Sinico

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The psychological present has an actual extension. When a sequence of instantaneous stimuli falls in this short interval of time, observers perceive a compresence of events in succession and the temporal order depends on the qualitative relationships between the perceptual properties of the events. Two experiments were carried out to study the influence of perceptual grouping, with and without temporal displacement, on the duration of auditory sequences. The psychophysical method of adjustment was adopted. The first experiment investigated the effect of temporal displacement of a white noise on sequence duration. The second experiment investigated the effect of temporal displacement, along the pitch dimension, on temporal shortening of sequence. The results suggest that the temporal order of sounds, in the case of temporal displacement, is organized along the pitch dimension.

Keywords: time perception, perceptual present, temporal displacement, Gestalt laws of perceptual organization

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Authors: Veronique Jubera, Guillaume Salek, Manuel Gaudon, Alain Garcia, Alain Demourgues

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Luminescence of transition metal and rare earth elements cover ultraviolet to far infrared wavelengths. Applications of phosphors are numerous. One can cite lighting, sensing, laser, energy, medical or military applications. But regarding each domain, specific criteria are required and they can be achieved with a strong control of the chemical composition. Emission of doped materials can be tailored with modifications of the local environment of the cations. For instance, the increase of the crystal field effect shifts the divalent manganese radiative transitions from the green to the red color. External factor as heat-treatment can induce changes of the doping element location or modify the unit cell crystalline symmetry. By controlling carefully the synthesis route, it is possible to initiate emission shift and to establish the thermal history of a compound. We propose to demonstrate through the luminescence of divalent manganese and trivalent rare earth doped oxide, that it is possible to follow the thermal history of a material. After optimization of the synthesis route, structural and optical properties are discussed. Finally, thermal calibration graphs are successfully established on these doped compounds. This makes these materials promising probe for thermal sensing.

Keywords: emission, thermal sensing, transition metal, rare eath element

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Authors: Soroosh Torabi, Brad Berron, Ren Xu, Christine Trinkle

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Microfluidics integrated with 3D cell culture is a powerful technology to mimic cellular environment, and can be used to study cell activities such as proliferation, migration and response to drugs. This technology has gained more attention in cancer studies over the past years, and many organ-on-a-chip systems have been developed to study cancer cell behaviors in an ex-vivo tumor microenvironment. However, there are still some barriers to adoption which include low throughput, complexity in 3D cell culture integration and limitations on non-optical analysis of cells. In this study, a user-friendly microfluidic multi-well plate was developed to mimic the in vivo tumor microenvironment. The microfluidic platform feeds multiple 3D cell culture sites at the same time which enhances the throughput of the system. The platform uses hydrophobic Cassie-Baxter surfaces created by microchannels to enable convenient loading of hydrogel/cell suspensions into the device, while providing barrier free placement of the hydrogel and cells adjacent to the fluidic path. The microchannels support convective flow and diffusion of nutrients to the cells and a removable lid is used to enable further chemical and physiological analysis on the cells. Different breast cancer cell lines were cultured in the device and then monitored to characterize nutrient delivery to the cells as well as cell invasion and proliferation. In addition, the drug response of breast cancer cell lines cultured in the device was compared to the response in xenograft models to the same drugs to analyze relevance of this platform for use in future drug-response studies.

Keywords: microfluidics, multi-well 3d cell culture, tumor microenvironment, tumor-on-a-chip

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Authors: Martin Kendra, Jaroslav Mašek, Juraj Čamaj, Matej Babin

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The railway transport is considered as a one of the most environmentally friendly mode of transport. With future prediction of increasing of freight transport there are lines facing problems with demanded capacity. Increase of the track capacity could be achieved by infrastructure constructive adjustments. The contribution shows how the travel time can be minimized and the track capacity increased by changing some of the basic infrastructure and operation parameters, for example, the minimal curve radius of the track, the number of tracks, or the usable track length at stations. Calculation of the necessary parameter changes is based on the fundamental physical laws applied to the train movement, and calculation of the occupation time is dependent on the changes of controlling the traffic between the stations.

Keywords: curve radius, maximum curve speed, track mass capacity, reconstruction

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Authors: Hyon I. Paek, Sang Rim Kim, Hyon A. Ryu

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In functional linear regression, one typical problem is to reduce dimension. Compared with multivariate linear regression, functional linear regression is regarded as an infinite-dimensional case, and the main task is to reduce dimensions of functional response and functional predictors. One common approach is to adapt functional principal component analysis (FPCA) on functional predictors and then use a few leading functional principal components (FPC) to predict the functional model. The leading FPCs estimated by the typical FPCA explain a major variation of the functional predictor, but these leading FPCs may not be mostly correlated with the functional response, so they may not be significant in the prediction for response. In this paper, we propose a supervised functional principal component analysis method for a functional response model with FPCs obtained by considering the correlation of the functional response. Our method would have a better prediction accuracy than the typical FPCA method.

Keywords: supervised, functional principal component analysis, functional response, functional linear regression

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Authors: Jessica Morales Perdomo, Daniel Rodriguez Caicedo, Fernando Cantor Rincon

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Tuta absoluta known as the tomato leaf miner, is one of the main pests in tomato crops in South America and the main pest in many European countries. Apanteles gelechiidivoris is a parasitoid of third instar Tuta absoluta larvae. Our studies have demonstrated that this parasitoid can cause up to 80% mortality of T. absoluta larvae in the field. We investigated cold storage of A. gelechiidivoris pupae as a method of mass production of this parasitoid. This storage method does not interfere with biological characteristics of the parasitoid. In this study, we evaluated the effect of different temperatures (4, 8 and 12°C) and different time duration (7, 14, 21 or 28 days) of cold storage on biological parameters of A. gelechiidivoris pupae and adults. The biological parameters of the parasitoid evaluated were: adult emergence time, lifespan, parasitism percentage and sex ratio. We found that the adult emergence time was delayed when the parasitoid pupae were stored at 4°C and 8°C. The shortest adult emergence was recorded when pupae were stored for seven days. The lowest adult emergence was found for pupae stored at 4°C and decreased significantly as the days of storage increased. We found high percentages of adult emergence when pupae were stored at 8°C and 12°C for seven days. Adult lifespan decreased with increasing days of cold storage. Adults emerging from pupae stored at 8°C during seven and 14 days showed the longest lifespan (nine days). The lowest parasitism rate was recorded at 4°C at every time point. The highest percentage of parasitism (80%) was found at 8°C during seven days of storage. The treatments had no effect on adults the sex ratio. The results suggest that A. gelechiidivoris pupae can be stored for up to 14 days at 8°C without affecting the efficacy of the parasitoid in the field.

Keywords: biological control, cold storage, massive rearing, quality control

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Authors: Ons Triki, Fathi Abid

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Along with the increase in the use of leasing contracts in corporate finance, multiple studies aim to model the credit risk of the lease in order to cover the losses of the lessor of the asset if the lessee goes bankrupt. In the current research paper, a convertible lease contract is elaborated in a continuous time stochastic universe aiming to ensure the financial stability of the firm and quickly recover the losses of the counterparties to the lease in case of default. This work examines the term structure of the lease rates taking into account the credit default risk and the capital structure of the firm. The interaction between the lessee's capital structure and the equilibrium lease rate has been assessed by applying the competitive lease market argument developed by Grenadier (1996) and the endogenous structural default model set forward by Leland and Toft (1996). The cumulative probability of default was calculated by referring to Leland and Toft (1996) and Yildirim and Huan (2006). Additionally, the link between lessee credit risk and lease rate was addressed so as to explore the impact of convertible lease financing on the term structure of the lease rate, the optimal leverage ratio, the cumulative default probability, and the optimal firm value by applying an endogenous conversion threshold. The numerical analysis is suggestive that the duration structure of lease rates increases with the increase in the degree of the market price of risk. The maximal value of the firm decreases with the effect of the optimal leverage ratio. The results are indicative that the cumulative probability of default increases with the maturity of the lease contract if the volatility of the asset service flows is significant. Introducing the convertible lease contract will increase the optimal value of the firm as a function of asset volatility for a high initial service flow level and a conversion ratio close to 1.

Keywords: convertible lease contract, lease rate, credit-risk, capital structure, default probability

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Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

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Authors: Aleksandra BužArovska, Gordana Bogoeva Gaceva

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Biodegradable polymers have received significant scientific attention in tissue engineering (TE) application, in particular their composites consisting of inorganic nanoparticles. In the last 15 years, they are subject of intensive research by many groups, aiming to develop polymer scaffolds with defined biodegradability, porosity and adequate mechanical stability. The most important characteristic making these materials attractive for TE is their biodegradability, a process that could be time controlled and long enough to enable generation of a new tissue as a replacement for the degraded polymer scaffold. In this work poly(L-lactic acid) scaffolds, filled with TiO2 nanoparticles functionalized with oleic acid, have been prepared by thermally induced phase separation method (TIPS). The functionalization of TiO2 nanoparticles with oleic acid was performed in order to improve the nanoparticles dispersibility within the polymer matrix and at the same time to inhibit the cytotoxicity of the nanofiller. The oleic acid was chosen as amphiphilic molecule belonging to the fatty acid family because of its non-toxicity and possibility for mediation between the hydrophilic TiO2 nanoparticles and hydrophobic PLA matrix. The produced scaffolds were characterized with thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), scanning electron microscopy (SEM) and mechanical compression measurements. The bioactivity for bone tissue engineering application was tested in supersaturated simulated body fluid. The degradation process was followed by Fourier transform infrared spectroscopy (FTIR). The results showed anisotropic morphology with elongated open pores (100 µm), high porosity (around 92%) and perfectly dispersed nanofiller. The compression moduli up to 10 MPa were identified independent on the nanofiller content. Functionalized TiO2 nanoparticles induced formation of hydroxyapatite clusters as much as unfunctionalized TiO2. The prepared scaffolds showed properties ideal for scaffold vascularization, cell attachment, growth and proliferation.

Keywords: biodegradation, bone tissue engineering, mineralization, PLA scaffolds

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Authors: Imen Aribi Ben Amor

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The aim of the present study is to analyze the performance of requests in emails among a group of Tunisian postgraduate students. It also seeks to determine the influence of the social factors on the participants’ requests performance. For this purpose, the data were collected using a discourse completion test (DCT). Accordingly, 42 Tunisian postgraduate students were asked to respond in English to eight different situations in which they carried out the speech act of request in emails. The data were analyzed based on the degree of directness. A detailed analysis of the head acts found in the DCT revealed that Tunisian Postgraduate students use a varied repertoire of request strategies (direct, conventionally indirect and non-conventionally indirect) but at the same time rely heavily on direct request strategies. They tended to address their requestees directly except for distant superiors. DCT results suggest that the participants are to some extent aware of the influence of the ranking of imposition and social distance but fail to acknowledge the weight of social power when performing requests in emails. The preference of the participants to use direct strategies may be the result of the effect of Tunisian culture and the negative transfer of Tunisian communicative strategies. Accordingly, this study suggests some pedagogical implications and suggestions for Tunisian EFL (English as a Foreign Language) instructors. They are required to pay closer attention to the pragmalinguistic nuances of the ways in which requests in emails are realized. Teachers can also help students understand academic email etiquettes by explicitly explaining what they expect in the student email. Thus, EFL teachers and syllabus designers should devote more attention to developing EFL learners’ pragmatic competence through teaching L2 pragmatics.

Keywords: directness, ranking of imposition, request strategies, social distance, social power

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Authors: Chang-Jen Lan

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Current Level of Service (LOS) index adopted in Highway Capacity Manual (HCM) for signalized intersections on surface streets is based on the intersection average delay. The delay thresholds for defining LOS grades are subjective and is unrelated to critical traffic condition. For example, an intersection delay of 80 sec per vehicle for failing LOS grade F does not necessarily correspond to the intersection capacity. Also, a specific measure of average delay may result from delay minimization, delay equality, or other meaningful optimization criteria. To that end, a reliability version of the intersection critical degree of saturation (v/c) as the LOS index is introduced. Traditionally, the level of saturation at a signalized intersection is defined as the ratio of critical volume sum (per lane) to the average saturation flow (per lane) during all available effective green time within a cycle. The critical sum is the sum of the maximal conflicting movement-pair volumes in northbound-southbound and eastbound/westbound right of ways. In this study, both movement volume and saturation flow are assumed log-normal distributions. Because, when the conditions of central limit theorem obtain, multiplication of the independent, positive random variables tends to result in a log-normal distributed outcome in the limit, the critical degree of saturation is expected to be a log-normal distribution as well. Derivation of the risk index predictive limits is complex due to the maximum and absolute value operators, as well as the ratio of random variables. A fairly accurate functional form for the predictive limit at a user-specified significant level is yielded. The predictive limit is then compared with the designated LOS thresholds for the intersection critical degree of saturation (denoted as X

Keywords: reliability analysis, level of service, intersection critical degree of saturation, risk based index

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Authors: Karl Eddie T. Malabanan

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Due to the quick transmission and public health risk of coronavirus disease, schools and universities have shifted to distant learning. Teachers everywhere were forced to shift gears instantly in order to react to the needs of students and families using synchronous and asynchronous virtual teaching. This study aims to explore the lived experiences of physical education teachers who are currently experiencing remote learning in teaching during the time of the COVID-19 pandemic. Specifically, the challenges that the physical education teachers encounter during remote learning and teaching. The participants include 12 physical education teachers who have taught in higher education institutions for at least five years. The researcher utilized qualitative research; specifically, the researcher used Consensual Qualitative Research (CQR). The results of this study showed that there are five categories for the Lived Experiences of Physical Education Teachers with thirty-one subcategories. This study revealed that physical education teachers experienced very challenging situations during the time of the pandemic. It also found that students had challenges in the abrupt transition from traditional to virtual learning classes, but it also showed that students are tenacious and willing to face any adversity. The researcher also finds that teachers are mentally drained during this time. Furthermore, one of the main focuses for the teachers should be on improving their well-being. And lastly, to cope with the challenges, teachers employ socializing to relieve tension and anxiety.

Keywords: lived experiences, consensual qualitative research, pandemic, education

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Authors: Punwath Prum

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Superfund site is recognized publicly to be a severe environmental problem to surrounding communities and biodiversity due to its hazardous chemical waste from industrial activities. It contaminates the soil and water but also is a leading potential point-source pollution affecting ecosystem in watershed areas from chemical substances. The risks of Superfund site on watershed can be effectively measured by utilizing publicly available data and geospatial analysis by free and open source application. This study analyzed the vegetation change within high risked contaminated watersheds in Wisconsin. The high risk watersheds were measured by which watershed contained high number Superfund sites. The study identified two potential risk watersheds in Lafayette and analyzed the temporal changes of vegetation within the areas based on Normalized difference vegetation index (NDVI) analysis. The raster statistic was used to compare the change of NDVI value over the period. The analysis results showed that the NDVI value within the Superfund sites’ boundary has a significant lower value than nearby surrounding and provides an analogy for environmental hazard affect by the chemical contamination in Superfund site.

Keywords: soil contamination, spatial analysis, watershed

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Authors: Perminder JitKaur, Santosh Satya, K. K. Pant, S. N. Naik

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Bamboo is extensively used in construction industry. Low durability of bamboo due to fungus infestation and termites attack under storage puts certain constrains for it usage as modern structural material. Looking at many chemical formulations for bamboo treatment leading to severe harmful environment effects, research on eco-friendly preservatives for bamboo treatment has been initiated world-over. In the present studies, eco-friendly preservative for bamboo treatment has been developed. To validate its application for structural purposes, investigation of effect of treatment on compressive strength has been investigated. Neem oil(25%) integrated with copper naphthenate (0.3%) on dilution with kerosene oil impregnated into bamboo culm at 2 bar pressure, has shown weight loss of only 3.15% in soil block analysis method. The results of compressive strength analysis using The results from compressive strength analysis using HEICO Automatic Compression Testing Machine, reveal that preservative treatment has not altered the structural properties of bamboo culms. Compressive strength of control (11.72 N/mm2) and above treated samples (11.71 N/mm2) was found to be comparable.

Keywords: D. strictus, bamboo, neem oil, presure treatment, compressive strength

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Authors: Lin Li, P. G. R. N. I. Pussella

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When representing spatial data and their attributes on different types of maps, the scale plays a key role in the process of map generalization. The process is consisted with two main operators such as selection and omission. Once some data were selected, they would undergo of several geometrical changing processes such as elimination, simplification, smoothing, exaggeration, displacement, aggregation and size reduction. As a result of these operations at different levels of data, the geometry of the spatial features such as length, sinuosity, orientation, perimeter and area would be altered. This would be worst in the case of preparation of small scale maps, since the cartographer has not enough space to represent all the features on the map. What the GIS users do is when they wanted to analyze a set of spatial data; they retrieve a data set and does the analysis part without considering very important characteristics such as the scale, the purpose of the map and the degree of generalization. Further, the GIS users use and compare different maps with different degrees of generalization. Sometimes, GIS users are going beyond the scale of the source map using zoom in facility and violate the basic cartographic rule 'it is not suitable to create a larger scale map using a smaller scale map'. In the study, the effect of map generalization for GIS analysis would be discussed as the main objective. It was used three digital maps with different scales such as 1:10000, 1:50000 and 1:250000 which were prepared by the Survey Department of Sri Lanka, the National Mapping Agency of Sri Lanka. It was used common features which were on above three maps and an overlay analysis was done by repeating the data with different combinations. Road data, River data and Land use data sets were used for the study. A simple model, to find the best place for a wild life park, was used to identify the effects. The results show remarkable effects on different degrees of generalization processes. It can see that different locations with different geometries were received as the outputs from this analysis. The study suggests that there should be reasonable methods to overcome this effect. It can be recommended that, as a solution, it would be very reasonable to take all the data sets into a common scale and do the analysis part.

Keywords: generalization, GIS, scales, spatial analysis

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Authors: Daniele Lerede, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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The European Green Deal is the first internationally agreed set of measures to contrast climate change and environmental degradation. Besides the main target of reducing emissions by at least 55% by 2030, it sets the target of accompanying European countries through an energy transition to make the European Union into a modern, resource-efficient, and competitive net-zero emissions economy by 2050, decoupling growth from the use of resources and ensuring a fair adaptation of all social categories to the transformation process. While the general purpose to allow the realization of the purposes of the Green Deal already dates back to 2019, strategies and policies keep being developed coping with recent circumstances and achievements. However, general long-term measures like the Circular Economy Action Plan, the proposals to shift from fossil natural gas to renewable and low-carbon gases, in particular biomethane and hydrogen, and to end the sale of gasoline and diesel cars by 2035, will all have significant effects on energy supply and demand evolution across the next decades. The interactions between energy supply and demand over long-term time frames are usually assessed via energy system models to derive useful insights for policymaking and to address technological choices and research and development. TEMOA-Europe is a newly developed energy system optimization model instance based on the minimization of the total cost of the system under analysis, adopting a technologically integrated, detailed, and explicit formulation and considering the evolution of the system in partial equilibrium in competitive markets with perfect foresight. TEMOA-Europe is developed on the TEMOA platform, an open-source modeling framework totally implemented in Python, therefore ensuring third-party verification even on large and complex models. TEMOA-Europe is based on a single-region representation of the European Union and EFTA countries on a time scale between 2005 and 2100, relying on a set of assumptions for socio-economic developments based on projections by the International Energy Outlook and a large technological dataset including 7 sectors: the upstream and power sectors for the production of all energy commodities and the end-use sectors, including industry, transport, residential, commercial and agriculture. TEMOA-Europe also includes an updated hydrogen module considering its production, storage, transportation, and utilization. Besides, it can rely on a wide set of innovative technologies, ranging from nuclear fusion and electricity plants equipped with CCS in the power sector to electrolysis-based steel production processes and steel in the industrial sector – with a techno-economic characterization based on public literature – to produce insightful energy scenarios and especially to cope with the very long analyzed time scale. The aim of this work is to examine in detail the scheme of measures and policies for the realization of the purposes of the Green Deal and to transform them into a set of constraints and new socio-economic development pathways. Based on them, TEMOA-Europe will be used to produce and comparatively analyze scenarios to assess the consequences of Green Deal-related measures on the future evolution of the energy mix over the whole energy system in an economic optimization environment.

Keywords: European Green Deal, energy system optimization modeling, scenario analysis, TEMOA-Europe

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Authors: S. Karklina, I. Erins

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The main problem is that there is a very low innovation performance in Latvia. Since Latvia is a Member State of European Union, it also shall have to fulfill the set targets and to improve innovative results. Universities are one of the main performers to provide innovative capacity of country. University, industry and government need to cooperate for getting best results. The intellectual property is one of the indicators to determine innovation level in the country or organization and patents are one of the characteristics of intellectual property. The objective of the article is to determine indicators characterizing innovative environment in Latvia and influence of the development of universities on them. The methods that will be used in the article to achieve the objectives are quantitative and qualitative analysis of the literature, statistical data analysis, and graphical analysis methods.

Keywords: HEI, innovations, Latvia, patents

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Authors: Justyna Żywiołek, Marek Matulewski

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Data, is information processed by enterprises for primary and secondary purposes as processes. Thanks to processing, the sales process takes place; in the case of the surveyed companies, sales take place online. However, this indirect form of contact with the customer causes many problems for both customers and furniture manufacturers. The article presents solutions that would solve problems related to the analysis of data and information in the order fulfillment process sent to post-warranty service. The article also presents an analysis of threats to the security of this information, both for customers and the enterprise.

Keywords: ordering furniture online, information security, furniture industry, enterprise security, risk analysis

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Authors: K. M. Shahunja, Peter D. Sly, Tahmina Begum, Tuhin Biswas, Abdullah Mamun

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Background: Various associations between different environmental exposures and asthma have been reported in different countries and populations. We aimed to investigate the associations between family, neighbourhood, and psychosocial environmental factors and asthma in Australia by conducting a systematic review and meta-analysis. Methods: We analysed the primary research studies conducted in Australia across multiple databases, including PubMed, EMBASE, and Scopus, and published between 2000 and 2020. The reviews and analyses focused on the overall association of different environmental exposures with the development or exacerbation of asthma symptoms or asthma-related hospital visits. Quality-effect meta-analysis was done to estimate the pooled odds ratio for different environmental exposures for asthma symptoms. Findings: Among the 4,799 unique published articles found, 46 were included here for systematic review and 28 for meta-analysis. Our review found that psychosocial factors, including low socioeconomic condition, maternal depression, mental stress, ethnicity, and discrimination, are associated with asthma symptoms. Pooled analysis was conducted on family and neighbourhood environmental factors and revealed that environmental tobacco smoking (ETS) (OR 1·69, 95% CI 1·19–2.38), synthetic bedding (OR 1·91, 95% CI 1·48–2·47) and gas heaters (OR 1·40, 95% CI 1·12–1·76) had significant overall associations with asthma-symptoms in Australia. Conclusion: Although the studies were heterogeneous, both systematic review and meta-analysis found several psychosocial and family environmental exposures to be significantly associated with asthma symptoms. Further study to identify their causal relationship and modification may reduce asthma symptoms in the Australian population.

Keywords: asthma, Australia, environment, systematic review

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Authors: Khamael Abualnaja, Hala M. Abo-Dief

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Silver nanoparticles (AgNPs) are the subject of important recent interest, present in a large range of applications such as electronics, catalysis, chemistry, energy, and medicine. Metallic nanoparticles are traditionally synthesized by wet chemical techniques, where the chemicals used are quite often toxic and flammable. In this work, we describe an effective and environmental-friendly technique of green synthesis of silver nanoparticles. Silver nanoparticles (AgNPs) synthesized using silver nitrate solution and the extract of mint, basil, orange peel and Tangerines peel which used as reducing agents. Silver Nanoparticles were characterized using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and UV–Vis absorption spectroscopy. SEM analysis showed the average particle size of mint, basil, orange peel, Tangerines peel are 30, 20, 12, 10 nm respectively. This is for the first time that any plant extract was used for the synthesis of nanoparticles.

Keywords: silver nanoparticles, green synthesis, scanning electron microscopy, plants

Procedia PDF Downloads 242

Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: Tabrej Khan

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Examination Scheduling System (ESS) is a scheduling system that targets as an exam committee in any academic institute to help them in managing the exams automatically. We present an algorithm for Examination Scheduling System. Nowadays, many universities have challenges with creating examination schedule fast with less confliction compared to hand works. Our aims are to develop a computerized system that can be used in examination scheduling in an academic institute versus available resources (Time, Hall, Invigilator and instructor) with no contradiction and achieve fairness among students. ESS was developed using HTML, C# language, Crystal Report and ASP.NET through Microsoft Visual Studio 2010 as developing tools with integrated SQL server database. This application can produce some benefits such as reducing the time spent in creating an exam schedule and achieving fairness among students

Keywords: examination scheduling system (ESS), algorithm, ASP.NET, crystal report

Procedia PDF Downloads 386

Authors: Jianliang Xu, Zhenghua Dai, Zhongjie Shen, Haifeng Liu, Fuchen Wang

Abstract:

In an entrained flow gasifier, the combustible components are converted into the gas phase, and the mineral content is converted into ash. Most of the ash particles or droplets are deposited on the refractory or membrane wall and form a slag layer that flows down to the quenching system. The captured particle reaction process and slag flow and phase transformation play an important role in gasifier performance and safe and stable operation. The reaction characteristic of captured char particles on the molten slag had been studied by applied a high-temperature stage microscope. The gasification process of captured chars with CO2 on the slag surface was observed and recorded, compared to the original char gasification. The particle size evolution, heat transfer process are discussed, and the gasification reaction index of the capture char particle are modeled. Molten slag layer promoted the char reactivity from the analysis of reaction index, Coupled with heat transfer analysis, shrinking particle model (SPM) was applied and modified to predict the gasification time at carbon conversion of 0.9, and results showed an agreement with the experimental data. A comprehensive model with gas-particle-slag flow and reaction models was used to model the different industry gasifier. The carbon conversion information in the spatial space and slag layer surface are investigated. The slag flow characteristic, such as slag velocity, molten slag thickness, slag temperature distribution on the membrane wall and refractory brick are discussed.

Keywords: char, slag, numerical simulation, gasification, wall reaction, membrane wall

Procedia PDF Downloads 292