Search results for: clotting time test

Authors: Hee Jae Shin, Lee Ku Kwac, In Pyo Cha, Min Sang Lee, Hyun Kyung Yoon, Hong Gun Kim

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In rapid industrial development has increased the demand for high-strength and lightweight materials. Thus, various CFRP (Carbon Fiber Reinforced Plastics) with composite materials are being used. The design variables of CFRP are its lamination direction, order, and thickness. Thus, the hardness and strength of CFRP depend much on their design variables. In this paper, the lamination direction of CFRP was used to produce a symmetrical ply [0°/0°, -15°/+15°, -30°/+30°, -45°/+45°, -60°/+60°, -75°/+75°, and 90°/90°] and an asymmetrical ply [0°/15°, 0°/30°, 0°/45°, 0°/60° 0°/75°, and 0°/90°]. The bending flexure stress of the CFRP specimen was evaluated through a bending test. Its thermal property was measured using an infrared camera. The symmetrical specimen and the asymmetrical specimen were analyzed. The results showed that the asymmetrical specimen increased the bending loads according to the increase in the orientation angle; and from 0°, the symmetrical specimen showed a tendency opposite the asymmetrical tendency because the tensile force of fiber differs at the vertical direction of its load. Also, the infrared camera showed that the thermal property had a trend similar to that of the mechanical properties.

Keywords: Carbon Fiber Reinforced Plastic (CFRP), bending test, infrared camera, composite

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Authors: Mustapha Yakubu, Ahmed Usman, Hashim Ambursa

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This paper presents the findings of a research which sought to investigate techniques used to improve cost and time control of construction projects management practice in Nigeria. However, there is limited research on issues surrounding the practical usage of these techniques. Data were collected through a questionnaire distributed to construction experts through a survey conducted on the 100 construction organisations and 50 construction consultancy firms in the Nigeria aimed at identifying common project cost and time control practices and factors inhibiting effective project control in practice. The study reveals that despite the vast application of control techniques a high proportion of respondents still experienced cost and time overruns on a significant proportion of their projects. Analysis of the survey results concluded that more effort should be geared at the management of the identified top project control inhibiting factors. This paper has outlined some measures for mitigating these inhibiting factors so that the outcome of project time and cost control can be improved in practice.

Keywords: construction project, cost control, Nigeria, time control

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Authors: Jin Y. Park, Jeong Wan Lee

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An experimental and analytical research on shear buckling of a comparably large polymer composite I-section is presented. It is known that shear buckling load of a large span composite beam is difficult to determine experimentally. In order to sensitively detect shear buckling of the tested I-section, twenty strain rosettes and eight displacement sensors were applied and attached on the web and flange surfaces. The tested specimen was a pultruded composite beam made of vinylester resin, E-glass, carbon fibers and micro-fillers. Various coupon tests were performed before the shear buckling test to obtain fundamental material properties of the I-section. An asymmetric four-point bending loading scheme was utilized for the shear test. The loading scheme resulted a high shear and almost zeros moment condition at the center of the web panel. The shear buckling load was successfully determined after analyzing the obtained test data from strain rosettes and displacement sensors. An analytical approach was also performed to verify the experimental results and to support the discussed experimental program.

Keywords: strain sensor, displacement sensor, shear buckling, polymer composite I-section, asymmetric loading

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Authors: Eugene Y. J. Aw, J. W. Koh, S. H. Chew, K. E. Chua, P. L. Goh, Grace H. B. Foo, M. L. Leong

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This paper presents the evaluation of various soil testing methods such as the four-probe soil electrical resistivity method and cone penetration test (CPT) that can complement a newly developed novel rapid soil classification scheme using computer vision, to improve the accuracy and productivity of on-site classification of excavated soil. In Singapore, excavated soils from the local construction industry are transported to Staging Grounds (SGs) to be reused as fill material for land reclamation. Excavated soils are mainly categorized into two groups (“Good Earth” and “Soft Clay”) based on particle size distribution (PSD) and water content (w) from soil investigation reports and on-site visual survey, such that proper treatment and usage can be exercised. However, this process is time-consuming and labor-intensive. Thus, a rapid classification method is needed at the SGs. Four-probe soil electrical resistivity and CPT were evaluated for their feasibility as suitable additions to the computer vision system to further develop this innovative non-destructive and instantaneous classification method. The computer vision technique comprises soil image acquisition using an industrial-grade camera; image processing and analysis via calculation of Grey Level Co-occurrence Matrix (GLCM) textural parameters; and decision-making using an Artificial Neural Network (ANN). It was found from the previous study that the ANN model coupled with ρ can classify soils into “Good Earth” and “Soft Clay” in less than a minute, with an accuracy of 85% based on selected representative soil images. To further improve the technique, the following three items were targeted to be added onto the computer vision scheme: the apparent electrical resistivity of soil (ρ) measured using a set of four probes arranged in Wenner’s array, the soil strength measured using a modified mini cone penetrometer, and w measured using a set of time-domain reflectometry (TDR) probes. Laboratory proof-of-concept was conducted through a series of seven tests with three types of soils – “Good Earth”, “Soft Clay,” and a mix of the two. Validation was performed against the PSD and w of each soil type obtained from conventional laboratory tests. The results show that ρ, w and CPT measurements can be collectively analyzed to classify soils into “Good Earth” or “Soft Clay” and are feasible as complementing methods to the computer vision system.

Keywords: computer vision technique, cone penetration test, electrical resistivity, rapid and non-destructive, soil classification

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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Authors: V. B. Bastos, M. P. Lima, P. R. G. Kurka

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This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.

Keywords: simulation, visual navigation, mobile robot, data visualization

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Authors: Mohamed Saeed Ahmed Salman

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The ancient Egyptians used the stars to measure time or, in a more precise sense, as one of the astronomical means of measuring time. These methods differed throughout the historical ages. They began with simple observations of observing astronomical phenomena and watching them, such as observing the movements of the stars in the sky. The year, to know the days, nights, and other means used to help set the time when the sky overcast, and so the researcher tries through archaeological evidence to demonstrate the knowledge of the ancient Egyptian stars of heaven, and movements through the first pre-history. It is not believed that the astronomical information possessed by the Egyptian was limited, and simple, it was reaching a level of almost optimal in terms of importance, and the goal he wanted to reach the ancient Egyptian, and also help him to know the time, and the passage of time; which ended in finally trying to find a system of timing and calculation of time. It was noted that there were signs that the stellar creed was known, and prosperous, especially since the pre-family ages, and this is evident on the inscriptions that come back to that period. The Egyptian realized that some of the stars remain visible at night, The ancient Egyptian was familiar with the daily journey of the stars. This is what was adopted in many paragraphs of the texts of the pyramids and its references to the rise of the deceased king of the heavenly world between the stars of the eternal sky. It was noted that the ancient Egyptian link between the doctrine of the star, we find that the public The lunar was known to the ancient Egyptians, and sang it for two years, and the stellar solar; but it was based on the appearance of the star Sirius, and this is the first means used to measure time and know the calendar stars.

Keywords: ancient Egyptian, astronomical panels, Egyptian, astronomical

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Authors: Yasuyuki Takahashi, Maya Yamashita, Kyoko Saito

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In general, dynamic SPECT data acquisition needs a few minutes for one rotation. Thus, the time-activity curve (TAC) derived from the dynamic SPECT is relatively coarse. In order to effectively shorten the interval, between data points, we adopted a 180-degree interpolation method. This method is already used for reconstruction of the X-ray CT data. In this study, we applied this 180-degree interpolation method to SPECT and investigated its effectiveness.To briefly describe the 180-degree interpolation method: the 180-degree data in the second half of one rotation are combined with the 180-degree data in the first half of the next rotation to generate a 360-degree data set appropriate for the time halfway between the first and second rotations. In both a phantom and a patient study, the data points from the interpolated images fell in good agreement with the data points tracking the accumulation of 99mTc activity over time for appropriate region of interest. We conclude that data derived from interpolated images improves the apparent time resolution of dynamic SPECT.

Keywords: dynamic SPECT, time resolution, 180-degree interpolation method, 99mTc-GSA.

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Authors: Jinhoa Lee

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The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of carbon dioxide (CO2) emissions and energy use in affecting the economic output, this paper is an effort to fulfill the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption (using disaggregated energy sources: crude oil, coal, natural gas, electricity), CO2 emissions and gross domestic product (GDP) for Egypt using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Augmented Dickey-Fuller (ADF) test for stationarity, Johansen maximum likelihood method for co-integration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. The long-run equilibrium in the VECM suggests some negative impacts of the CO2 emissions and the coal and natural gas use on the GDP. Conversely, a positive long-run causality from the electricity consumption to the GDP is found to be significant in Egypt during the period. In the short-run, some positive unidirectional causalities exist, running from the coal consumption to the GDP, and the CO2 emissions and the natural gas use. Further, the GDP and the electricity use are positively influenced by the consumption of petroleum products and the direct combustion of crude oil. Overall, the results support arguments that there are relationships among environmental quality, energy use, and economic output in both the short term and long term; however, the effects may differ due to the sources of energy, such as in the case of Egypt for the period of 1980-2010.

Keywords: CO2 emissions, Egypt, energy consumption, GDP, time series analysis

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: V. A. Doss, R. Sowndarya, K. Juila Rose Mary

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Objective: Amino acid neurotransmitter system dysfunction plays a major role in the pathophysiology of depression. The objective of the present study was to identify the amino acids as possible metabolite biomarkers for depression using GCMS (Gas Chromatography Mass Spectrometry) before and after exercise regimen in brain samples of depression induced animal models. Methods: Depression-like behaviour was induced by Chronic Unpredictable mild stress (CUMS). Severity of depression was measured by forced swim test (FST) and sucrose consumption test (SCT). Swimming protocol was followed for 4 weeks of exercise treatment. Brain obtained from depressed and exercise treated rats were used for the metabolite analysis by GCMS. Subsequent statistical analysis obtained by ANOVA followed by post hoc test revealed significant metabolic changes. Results: Amino acids such as alanine, glycine, serine, glutamate, homocysteine, proline and branched chain aminoacids (BCAs) Leucine, Isoleucine, Valine were determined in brain samples of control, depressed and exercised groups. Among these amino acids, the levels of D-Serine and branched chain amino acids were found to be decreased in depression induced rats. After four weeks of swimming exercise regimen, there were improvements in the levels of serine and Branched chain amino acids. Conclusion: We suggest that Serine and BCAs may be investigated as potential metabolite markers using GCMS and their beneficial metabolic changes in Exercise.

Keywords: metabolomics, depression, forced swim test, exercise, amino acid metabolites, GCMS, biomarker

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Authors: Ziwen Fang, Jianran Wang, Hongtao Liu, Weiguo Kong, Kefei Wang, Qi Luo, Haifeng Hong

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A 4-stage crash energy management (CEM) system for subway rail vehicles used by Massachusetts Bay Transportation Authority (MBTA) in the USA is developed in this paper. The 4 stages of this new CEM system include 1) energy absorbing coupler (draft gear and shear bolts), 2) primary energy absorbers (aluminum honeycomb structured box), 3) secondary energy absorbers (crush tube), and 4) collision post and corner post. A sliding anti-climber and a fixed anti-climber are designed at the front of the vehicle cooperating with the 4-stage CEM to maximize the energy to be absorbed and minimize the damage to passengers and crews. In order to investigate the effectiveness of this CEM system, both finite element (FE) methods and crashworthiness test have been employed. The whole vehicle consists of 3 married pairs, i.e., six cars. In the FE approach, full-scale railway car models are developed and different collision cases such as a single moving car impacting a rigid wall, two moving cars into a rigid wall, two moving cars into two stationary cars, six moving cars into six stationary cars and so on are investigated. The FE analysis results show that the railway vehicle incorporating this CEM system has a superior crashworthiness performance. In the crashworthiness test, a simplified vehicle front end including the sliding anti-climber, the fixed anti-climber, the primary energy absorbers, the secondary energy absorber, the collision post and the corner post is built and impacted to a rigid wall. The same test model is also analyzed in the FE and the results such as crushing force, stress, and strain of critical components, acceleration and velocity curves are compared and studied. FE results show very good comparison to the test results.

Keywords: railway vehicle collision, crash energy management design, finite element method, crashworthiness test

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Authors: S. Yun, M. Kwak

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This study is about an aerodynamic brake device for a high-speed train. In order to apply an aerodynamic brake device, an influence of the aerodynamic brake device on a high-speed train was studied aerodynamically, acoustically and dynamically. Wind tunnel test was conducted to predict an effect of braking distance reduction with a scale model of 1/30. Aerodynamic drag increases by 244% with a brake panel of a 90 degree angle. Braking distance for an emergency state was predicted to decrease by 13%.

Keywords: aerodynamic brake, braking distance, drag coefficient, high-speed train, wind-tunnel test

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Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

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Passive sonar is a method for detecting acoustic signals in the ocean. It detects the acoustic signals emanating from external sources. With passive sonar, we can determine the bearing of the target only, no information about the range of the target. Target Motion Analysis (TMA) is a process to estimate the position and speed of a target using passive sonar information. Since bearing is the only available information, the TMA technique called Bearing-only TMA. Many TMA techniques have been developed. However, until now, there is not a very effective method that could be used to always track an unknown target and extract its moving trace. In this work, a design of effective Bearing-only TMA Algorithm is done. The measured bearing angles are very noisy. Moreover, for multi-beam sonar, the measurements is quantized due to the sonar beam width. To deal with this, modified gain extended Kalman filter algorithm is used. The algorithm is fine-tuned, and many modules are added to improve the performance. A special validation gate module is used to insure stability of the algorithm. Many indicators of the performance and confidence level measurement are designed and tested. A new method to detect if the target is maneuvering is proposed. Moreover, a reactive optimal observer maneuver based on bearing measurements is proposed, which insure converging to the right solution all of the times. To test the performance of the proposed TMA algorithm a simulation is done with a MATLAB program. The simulator program tries to model a discrete scenario for an observer and a target. The simulator takes into consideration all the practical aspects of the problem such as a smooth transition in the speed, a circular turn of the ship, noisy measurements, and a quantized bearing measurement come for multi-beam sonar. The tests are done for a lot of given test scenarios. For all the tests, full tracking is achieved within 10 minutes with very little error. The range estimation error was less than 5%, speed error less than 5% and heading error less than 2 degree. For the online performance estimator, it is mostly aligned with the real performance. The range estimation confidence level gives a value equal to 90% when the range error less than 10%. The experiments show that the proposed TMA algorithm is very robust and has low estimation error. However, the converging time of the algorithm is needed to be improved.

Keywords: target motion analysis, Kalman filter, passive sonar, bearing-only tracking

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: Javad Khaligh, Aghileh Heydari, Ali Akbar Heydari

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Mathematical epidemiological models for the spread of disease through a population are used to predict the prevalence of a disease or to study the impacts of treatment or prevention measures. Initial conditions for these models are measured from statistical data collected from a population since these initial conditions can never be exact, the presence of chaos in mathematical models has serious implications for the accuracy of the models as well as how epidemiologists interpret their findings. This paper confirms the chaotic behavior of a model for dengue fever and SI by investigating sensitive dependence, bifurcation, and 0-1 test under a variety of initial conditions.

Keywords: epidemiological models, SEIR disease model, bifurcation, chaotic behavior, 0-1 test

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Authors: Oyetunji John Adenuga

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This study on the comparative analysis of the performance of teachers in private and public schools was carried out in Ibadan North West Local Government Area of Oyo State. This study examined the justification for the claim that there is difference in the performance of teachers in private and public primary schools and at the same time identified factors responsible for the difference in the performance of these teachers. A descriptive survey research design was used for the study. Data generated were analysed using t-test and regression analysis. The findings of the study revealed that there is significant difference in the performance of teachers in private and private primary schools in Ibadan North West Local Government Area of Oyo State (t=64.09; df=459; p,.05). The findings also revealed that the method of teaching in private primary schools is significantly different from the method of teaching in public primary schools in Ibadan North West Local Government Area of Oyo State (t=73.08; df=459; p,.05). Findings revealed that school leadership and management have significant contribution on the performance of private and public primary school teachers in Ibadan North West Local Area of Oyo State. Based on the finding, the following recommendations were made: Primary school teachers need to be motivated and rewarded for excellent performance. Primary schools should be properly equipped with teaching-aid facilities, laboratories and libraries. Government should use the findings of this study to improve on teaching materials provided to the primary school teachers in Nigeria. Public primary schools should be designed by education planners, administrators and government. Headmasters, proprietors and teachers of primary schools should look inward and give a performance appraisal and evaluation of themselves form time to time based on subject they taught. Finally, school administrators should be conscious of the way they manage the teachers in schools not only in informal situations but also in formal settings.

Keywords: private education, public education, school leadership, school management, teachers performance

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Authors: Abhishek Kumar

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X70 pipeline steel was electrochemically charged with hydrogen for different durations in order to find crack nucleation and propagation sites. After 3 hours charging, suitable regions for crack initiation and propagation were found. These regions were studied by OM, SEM, EDS and later Vicker hardness test was done. The results brought out that HIC cracks nucleated from regions rich of inclusions and further propagated through the segregation area of some elements, such as manganese, carbon, silicon and sulfur. It is worth-mentioning that all these potential sites for crack nucleation and propagation appeared at the centre of cross section of the specimens. Additionally, cracked area has harder phase than the non-cracked area which was confirmed by hardness test.

Keywords: X70 steel, morphology of inclusions, SEM/EDS/OM, simulation, statistical data

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Authors: Kalsoom Rani

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Tobacco contains nicotine, which causes addiction to many toxic chemicals. In the world, people consume it in the form of smoke, chew, and sniffing, smoke of it is composed of almost 7000 active chemicals, which are very harmful to human health as well as for eye health, inhalation of tobacco smoke and fumes can accelerate and cause many blinding eye diseases. Dry eye and smoking have not been covered extensively in researches; more studies are required to unveil the relationship between smoking and dry eye. This study was conducted to determine the quantity and quality of tears in smokers. 60 subjects participated in the study, which was divided into two groups on the basis of consumption of cigarettes per day with age matched non smokers of 15-50 years. All participants have gone through a study based questioner, eye examination, and diagnostic 'Dry Eye Tests' for evaporative tears evaluation and measurement of basal tear secretion. Subjects were included in the criteria of 10 cigarettes per day with a minimum duration of 1 year; passive smokers for control groups were excluded. The study was carried out in a Medina Teaching Hospital, Faisalabad, Pakistan, ophthalmology department for the duration of 8 months. Mean values for tear break up time (TBUT), was reported 10sec with SD of +3.74 in controlled group, 5sec with SD + 2.32 in smokers and 4sec SD +3.77 heavy smokers in right eye (RE) and left eye (LE) 10.35sec with SD of +3.88 in controlled 5sec with SD + 2.3 in smokers and much reduced TBUT in heavy smokers was 3.85sec SD+2.20. Smoking has a very strong association with TRUT with a significance of P=.00 both eyes. Mean Schirmer-I value of the subjects was reported 12.6mm with SD + 8.37 in RE and 12.59mm with SD + 8.96 LE. The mean Schirmer-II test value was reported in the right, and left eye with a mean value for control was 20.23mm with SD + 8.93, 20.75mm with SD + 8.84 respectively, and in Smokers 9.90mm with SD + 5.74, and 10.07mm with SD + 6.98, and in heavy smokers 7.7mm, SD + 3.22 and 6.9, SD + 3.50 mm, association with smoking showed p=.001 in RE and .003 in LE. Smoking has deteriorated effect on both evaporative tear and aqueous tear secretion and causing symptoms of dry eye burning, itching, redness, and watering with epithelial cell damage.

Keywords: tear break-up time, basal tear secretion, smokers, dry eye

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Authors: Shahram Naghizadeh Raeisi, Ali Alghooneh

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The application of whey protein in drink industry to enhance the nutritional value of the products is important. Furthermore, the gelification of protein during thermal treatment and shelf life makes some limitations in its application. So, the main goal of this research is manufacturing of high concentrate whey protein orange drink with appropriate shelf life. In this way, whey protein was 5 to 30% hydrolyzed ( in 5 percent intervals at six stages), then thermal stability of samples with 10% concentration of protein was tested in acidic condition (T= 90 °C, pH=4.2, 5 minutes ) and neutral condition (T=120° C, pH:6.7, 20 minutes.) Furthermore, to study the shelf life of heat treated samples in 4 months at 4 and 24 °C, the time sweep rheological test were done. At neutral conditions, 5 to 20% hydrolyzed sample showed gelling during thermal treatment, whereas at acidic condition, was happened only in 5 to 10 percent hydrolyzed samples. This phenomenon could be related to the difference in hydrodynamic radius and zeta potential of samples with different level of hydrolyzation at acidic and neutral conditions. To study the gelification of heat resistant protein solutions during shelf life, for 4 months with 7 days intervals, the time sweep analysis were performed. Cross over was observed for all heat resistant neutral samples at both storage temperature, while in heat resistant acidic samples with degree of hydrolysis, 25 and 30 percentage at 4 and 20 °C, it was not seen. It could be concluded that the former sample was stable during heat treatment and 4 months storage, which made them a good choice for manufacturing high protein drinks. The Scheffe polynomial model and numerical optimization were employed for modeling and high protein orange drink formula optimization. Scheffe model significantly predicted the overal acceptance index (Pvalue<0.05) of sensorial analysis. The coefficient of determination (R2) of 0.94, the adjusted coefficient of determination (R2Adj) of 0.90, insignificance of the lack-of-fit test and F value of 64.21 showed the accuracy of the model. Moreover, the coefficient of variable (C.V) was 6.8% which suggested the replicability of the experimental data. The desirability function had been achieved to be 0.89, which indicates the high accuracy of optimization. The optimum formulation was found as following: Modified whey protein solution (65.30%), natural orange juice (33.50%), stevia sweetener (0.05%), orange peel oil (0.15%) and citric acid (1 %), respectively. Its worth mentioning that this study made an appropriate model for application of whey protein in drink industry without bitter flavor and gelification during heat treatment and shelf life.

Keywords: croos over, orange beverage, protein modification, optimization

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Authors: Girish Chavadappanavar

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The impact of climate on agriculture could result in problems with food security and may threaten the livelihood activities upon which much of the population depends. In the present study, the development of a statistical yield forecast model has been carried out for sugarcane production over Belagavi district, Karnataka using weather variables of crop growing season and past observed yield data for the period of 1971 to 2010. The study shows that this type of statistical yield forecast model could efficiently forecast yield 5 weeks and even 10 weeks in advance of the harvest for sugarcane within an acceptable limit of error. The performance of the model in predicting yields at the district level for sugarcane crops is found quite satisfactory for both validation (2007 and 2008) as well as forecasting (2009 and 2010).In addition to the above study, the climate variability of the area has also been studied, and hence, the data series was tested for Mann Kendall Rank Statistical Test. The maximum and minimum temperatures were found to be significant with opposite trends (decreasing trend in maximum and increasing in minimum temperature), while the other three are found in significant with different trends (rainfall and evening time relative humidity with increasing trend and morning time relative humidity with decreasing trend).

Keywords: climate impact, regression analysis, yield and forecast model, sugar models

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Authors: Soroush Pakniyat-Jahromi, Jessica Bucciarelli, Souparno Mitra, Neda Motamedi, Ralph Amazan, Samuel Rothman, Jose Tiburcio, Douglas Reich, Vicente Liz

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Violence is defined as an act of physical force that is intended to cause harm and may lead to physical and/or psychological damage. Violence toward healthcare workers (HCWs) is more common in psychiatric settings, emergency departments, and nursing homes; however, healthcare workers in medical setting are not spared from such events. Workplace violence has a huge burden in the healthcare industry and has a major impact on the physical and mental wellbeing of staff. The purpose of this study is to compare the prevalence of patient agitation and violence in medical-surgical settings in BronxCare Hospital (BCH) Bronx, New York, one year before and during the COVID-19 pandemic. Data collection occurred between June 2021 and August 2021, while the sampling time was from 2019 to 2021. The data were separated into two separate time categories: pre-COVID-19 (03/2019-03/2020) and COVID-19 (03/2020-03/2021). We created frequency tables for 19 variables. We used a chi-square test to determine a variable's statistical significance. We tested all variables against “restraint type”, determining if a patient was violent or became violent enough to restrain. The restraint types were “chemical”, “physical”, or both. This analysis was also used to determine if there was a statistical difference between the pre-COVID-19 and COVID-19 timeframes. Our data shows that there was an increase in incidents of violence in COVID-19 era (03/2020-03/2021), with total of 194 (62.8%) reported events, compared to pre COVID-19 era (03/2019-03/2020) with 115 (37.2%) events (p: 0.01). Our final analysis, completed using a chi-square test, determined the difference in violence in patients between pre-COVID-19 and COVID-19 era. We then tested the violence marker against restraint type. The result was statistically significant (p: 0.01). This is the first paper to systematically review the prevalence of violence in medical-surgical units in a hospital in New York, pre COVID-19 and during the COVID-19 era. Our data is in line with the global trend of increased prevalence of patient agitation and violence in medical settings during the COVID-19 pandemic. Violence and its management is a challenge in healthcare settings, and the COVID-19 pandemic has brought to bear a complexity of circumstances, which may have increased its incidence. It is important to identify and teach healthcare workers the best preventive approaches in dealing with patient agitation, to decrease the number of restraints in medical settings, and to create a less restrictive environment to deliver care.

Keywords: COVID-19 pandemic, patient agitation, restraints, violence

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Authors: Mingyue Sheng, Basil Sharp

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Greenhouse gas (GHG) emissions from national transport account for the largest share of emissions from energy use in New Zealand. Whether the environmental Kuznets curve (EKC) relationship exists between environmental degradation indicators from the transport sector and economic growth in New Zealand remains unclear. This paper aims at exploring the causality relationship between CO₂ emissions from the transport sector, fossil fuel consumption, and the Gross Domestic Product (GDP) per capita in New Zealand, using annual data for the period 1977 to 2013. First, conventional unit root tests (Augmented Dickey–Fuller and Phillips–Perron tests), and a unit root test with the breakpoint (Zivot-Andrews test) are employed to examine the stationarity of the variables. Second, the autoregressive distributed lag (ARDL) bounds test for co-integration, followed by Granger causality investigated causality among the variables. Empirical results of the study reveal that, in the short run, there is a unidirectional causality between economic growth and transport CO₂ emissions with direction from economic growth to transport CO₂ emissions, as well as a bidirectional causality from transport CO₂ emissions to road energy consumption.

Keywords: economic growth, transport carbon dioxide emissions, environmental Kuznets curve, causality

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Authors: Mariana Lima, Rodrigo Silva, Victor Stange, Teodiano Bastos

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Due to the high reliability reached by DNA tests, since the 1980s this kind of test has allowed the identification of a growing number of criminal cases, including old cases that were unsolved, now having a chance to be solved with this technology. Currently, the use of genetic profiling databases is a typical method to increase the scope of genetic comparison. Forensic laboratories must process, analyze, and generate genetic profiles of a growing number of samples, which require time and great storage capacity. Therefore, it is essential to develop methodologies capable to organize and minimize the spent time for both biological sample processing and analysis of genetic profiles, using software tools. Thus, the present work aims the development of a software system solution for laboratories of forensics genetics, which allows sample, criminal case and local database management, minimizing the time spent in the workflow and helps to compare genetic profiles. For the development of this software system, all data related to the storage and processing of samples, workflows and requirements that incorporate the system have been considered. The system uses the following software languages: HTML, CSS, and JavaScript in Web technology, with NodeJS platform as server, which has great efficiency in the input and output of data. In addition, the data are stored in a relational database (MySQL), which is free, allowing a better acceptance for users. The software system here developed allows more agility to the workflow and analysis of samples, contributing to the rapid insertion of the genetic profiles in the national database and to increase resolution of crimes. The next step of this research is its validation, in order to operate in accordance with current Brazilian national legislation.

Keywords: database, forensic genetics, genetic analysis, sample management, software solution

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Authors: Renato Morbidelli, Carla Saltalippi, Alessia Flammini, Marco Cifrodelli, Corrado Corradini

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The trend of magnitude and frequency of extreme rainfalls seems to be different depending on the investigated area of the world. In this work, the impact of climate change on extreme rainfalls in Umbria, an inland region of central Italy, is examined using data recorded during the period 1921-2015 by 10 representative rain gauge stations. The study area is characterized by a complex orography, with altitude ranging from 200 to more than 2000 m asl. The climate is very different from zone to zone, with mean annual rainfall ranging from 650 to 1450 mm and mean annual air temperature from 3.3 to 14.2°C. Over the past 15 years, this region has been affected by four significant droughts as well as by six dangerous flood events, all with very large impact in economic terms. A least-squares linear trend analysis of annual maximums over 60 time series selected considering 6 different durations (1 h, 3 h, 6 h, 12 h, 24 h, 48 h) showed about 50% of positive and 50% of negative cases. For the same time series the non-parametrical Mann-Kendall test with a significance level 0.05 evidenced only 3% of cases characterized by a negative trend and no positive case. Further investigations have also demonstrated that the variance and covariance of each time series can be considered almost stationary. Therefore, the analysis on the magnitude of extreme rainfalls supplies the indication that an evident trend in the change of values in the Umbria region does not exist. However, also the frequency of rainfall events, with particularly high rainfall depths values, occurred during a fixed period has also to be considered. For all selected stations the 2-day rainfall events that exceed 50 mm were counted for each year, starting from the first monitored year to the end of 2015. Also, this analysis did not show predominant trends. Specifically, for all selected rain gauge stations the annual number of 2-day rainfall events that exceed the threshold value (50 mm) was slowly decreasing in time, while the annual cumulated rainfall depths corresponding to the same events evidenced trends that were not statistically significant. Overall, by using a wide available dataset and adopting simple methods, the influence of climate change on the heavy rainfalls in the Umbria region is not detected.

Keywords: climate changes, rainfall extremes, rainfall magnitude and frequency, central Italy

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Authors: A. M. Tahsini

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Computational study of two dimensional supersonic reacting hydrogen-air flows is performed to investigate the nitrogen effects on ignition delay time for premixed and diffusion flames. Chemical reaction is treated using detail kinetics and the advection upstream splitting method is used to calculate the numerical inviscid fluxes. The results show that only in the stoichiometric condition for both premixed and diffusion flames, there is monotone dependency of the ignition delay time to the nitrogen addition. In other situations, the optimal condition from ignition viewpoint should be found using numerical investigations.

Keywords: diffusion flame, ignition delay time, mixing layer, numerical simulation, premixed flame, supersonic flow

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Authors: Khanh To Duc, Monica Chiogna, Gianfranco Adimari

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With three diagnostic categories, assessment of the performance of diagnostic tests is achieved by the analysis of the receiver operating characteristic (ROC) surface, which generalizes the ROC curve for binary diagnostic outcomes. The volume under the ROC surface (VUS) is a summary index usually employed for measuring the overall diagnostic accuracy. When the true disease status can be exactly assessed by means of a gold standard (GS) test, unbiased nonparametric estimators of the ROC surface and VUS are easily obtained. In practice, unfortunately, disease status verification via the GS test could be unavailable for all study subjects, due to the expensiveness or invasiveness of the GS test. Thus, often only a subset of patients undergoes disease verification. Statistical evaluations of diagnostic accuracy based only on data from subjects with verified disease status are typically biased. This bias is known as verification bias. Here, we consider the problem of correcting for verification bias when continuous diagnostic tests for three-class disease status are considered. We assume that selection for disease verification does not depend on disease status, given test results and other observed covariates, i.e., we assume that the true disease status, when missing, is missing at random. Under this assumption, we discuss several solutions for ROC surface analysis based on imputation and re-weighting methods. In particular, verification bias-corrected estimators of the ROC surface and of VUS are proposed, namely, full imputation, mean score imputation, inverse probability weighting and semiparametric efficient estimators. Consistency and asymptotic normality of the proposed estimators are established, and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations using real datasets are also given.

Keywords: imputation, missing at random, inverse probability weighting, ROC surface analysis

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Authors: May Khei Hu, Kevin Leong, Fu Siong Ng, Nicholas Peter

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Introduction: Sympathetic stimulation has been recognised as a potent stimulus of arrhythmogenesis in various cardiac pathologies, possibly by augmenting dispersion of repolarisation. The effects of sympathetic stimulation in healthy subjects however remain unclear. It is, therefore, crucial to first establish the effects of physiological stress on dispersion of repolarisation in healthy subjects before understanding these effects in pathological cardiac conditions. We hypothesised that activation-recovery interval (ARI; which is a surrogate of action potential duration) and dispersion of repolarisation decrease on sympathetic stimulation. Methods: Eight patients aged 18-55 years with structurally normal hearts underwent head-up tilt test (HUTT) and exercise tolerance test (ETT) while wearing the electrocardiographic imaging (ECGi) vest. Patients later underwent CT scan and the epicardial potentials are reconstructed using the ECGi software. Activation and recovery times were determined from the acquired electrograms. ARI was calculated and later corrected using Bazett’s formula. Global and regional dispersion of repolarisation were determined from standard deviation of the corrected ARI (ARIc). One-way analysis of variance (ANOVA) and Wilcoxon test were used to evaluate statistical significance. Results: Global ARIc increased significantly [p<0.01] when patients were tilted upwards but decreased significantly after five minutes [p<0.01]. A subsequent post- hoc analysis revealed that the decrease in R-R was more substantial compared to the change in ARI, resulting in the observed increase in ARIc. Global ARIc decreased on peak exercise [p<0.01] but increased on recovery [p<0.01]. Global dispersion increased significantly on peak exercise [p<0.05] although there were no significant changes in regional dispersion. There were no significant changes in both global and regional dispersion during tilt. Conclusion: ARIc decreases upon sympathetic stimulation in healthy subjects. Global dispersion of repolarisation increases upon exercise although there were no changes in global or regional dispersion during orthostatic stress.

Keywords: dispersion of repolarisation, sympathetic stimulation, Head-up tilt test (HUTT), Exercise tolerance test (ETT), Electrocardiographic imaging (ECGi)

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Authors: Anna-Lisa Osvalder, Jonas Borell

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There are several reasons behind the use, non-use, or inadequate use of personal protective equipment (PPE) in the construction industry. Comfort and accurate size support proper use, while discomfort, misfit, and difficulties to understand how the PPEs should be handled inhibit correct usage. The need for several protective equipments simultaneously might also create problems. The purpose of this study was to analyse the correct usage, comfort, and fit of different types of PPEs used for construction work. Correct usage was analysed as guessability, i.e., human perceptions of how to don, adjust, use, and doff the equipment, and if used as intended. The PPEs tested individually or in combinations were a helmet, ear protectors, goggles, respiratory masks, gloves, protective cloths, and safety harnesses. First, an analytical evaluation was performed with ECW (enhanced cognitive walkthrough) and PUEA (predictive use error analysis) to search for usability problems and use errors during handling and use. Then usability tests were conducted to evaluate guessability, comfort, and fit with 10 test subjects of different heights and body constitutions. The tests included observations during donning, five different outdoor work tasks, and doffing. The think-aloud method, short interviews, and subjective estimations were performed. The analytical evaluation showed that some usability problems and use errors arise during donning and doffing, but with minor severity, mostly causing discomfort. A few use errors and usability problems arose for the safety harness, especially for novices, where some could lead to a high risk of severe incidents. The usability tests showed that discomfort arose for all test subjects when using a combination of PPEs, increasing over time. For instance, goggles, together with the face mask, caused pressure, chafing at the nose, and heat rash on the face. This combination also limited sight of vision. The helmet, in combination with the goggles and ear protectors, did not fit well and caused uncomfortable pressure at the temples. No major problems were found with the individual fit of the PPEs. The ear protectors, goggles, and face masks could be adjusted for different head sizes. The guessability for how to don and wear the combination of PPE was moderate, but it took some time to adjust them for a good fit. The guessability was poor for the safety harness; few clues in the design showed how it should be donned, adjusted, or worn on the skeletal bones. Discomfort occurred when the straps were tightened too much. All straps could not be adjusted for somebody's constitutions leading to non-optimal safety. To conclude, if several types of PPEs are used together, discomfort leading to pain is likely to occur over time, which can lead to misuse, non-use, or reduced performance. If people who are not regular users should wear a safety harness correctly, the design needs to be improved for easier interpretation, correct position of the straps, and increased possibilities for individual adjustments. The results from this study can be a base for re-design ideas for PPE, especially when they should be used in combinations.

Keywords: construction work, PPE, personal protective equipment, misuse, guessability, usability

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Authors: Loubna Tani, Nabih Elouzzani

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Crosstalk among interconnects and printed-circuit board (PCB) traces is a major limiting factor of signal quality in high-speed digital and communication equipments especially when fast data buses are involved. Such a bus is considered as a planar multiconductor transmission line. This paper will demonstrate how the finite difference time domain (FDTD) method provides an exact solution of the transmission-line equations to analyze the near end and the far end crosstalk. In addition, this study makes it possible to analyze the rise time effect on the near and far end voltages of the victim conductor. The paper also discusses a statistical analysis, based upon a set of several simulations. Such analysis leads to a better understanding of the phenomenon and yields useful information.

Keywords: multiconductor transmission line, crosstalk, finite difference time domain (FDTD), printed-circuit board (PCB), rise time, statistical analysis

Procedia PDF Downloads 433