Search results for: super critical fluid extraction (SFE)

Authors: Duc V. Nguyen

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Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

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Authors: Arnaud Nougues

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This paper describes a two-stage methodology derived from internal model control (IMC) for tuning a proportional-integral-derivative (PID) controller for levels or other integrating processes in an industrial environment. Focus is the ease of use and implementation speed which are critical for an industrial application. Tuning can be done with minimum effort and without the need for time-consuming open-loop step tests on the plant. The first stage of the method applies to levels only: the vessel residence time is calculated from equipment dimensions and used to derive a set of preliminary proportional-integral (PI) settings with IMC. The second stage, re-tuning in closed-loop, applies to levels as well as other integrating processes: a tuning correction mechanism has been developed based on a series of closed-loop simulations with model errors. The tuning correction is done from a simple closed-loop step test and the application of a generic correlation between observed overshoot and integral time correction. A spin-off of the method is that an estimate of the vessel residence time (levels) or open-loop process gain (other integrating process) is obtained from the closed-loop data.

Keywords: closed-loop model identification, IMC-PID tuning method, integrating process control, on-line PID tuning adaptation

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Authors: Nasim Fallahi, Erasmo Carrera, Alfonso Pagani

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Variable angle tow describes the fibres which are curvilinearly steered in a composite lamina. Significantly, stiffness tailoring freedom of VAT composite laminate can be enlarged and enabled. Composite structures with curvilinear fibres have been shown to improve the buckling load carrying capability in contrast with the straight laminate composites. However, the optimal design and analysis of VAT are faced with high computational efforts due to the increasing number of variables. In this article, an efficient optimum solution has been used in combination with 1D Carrera’s Unified Formulation (CUF) to investigate the optimum fibre orientation angles for buckling analysis. The particular emphasis is on the LE-based CUF models, which provide a Lagrange Expansions to address a layerwise description of the problem unknowns. The first critical buckling load has been considered under simply supported boundary conditions. Special attention is lead to the sensitivity of buckling load corresponding to the fibre orientation angle in comparison with the results which obtain through the Genetic Algorithm (GA) optimization frame and then Artificial Neural Network (ANN) is applied to investigate the accuracy of the optimized model. As a result, numerical CUF approach with an optimal solution demonstrates the robustness and computational efficiency of proposed optimum methodology.

Keywords: beam structures, layerwise, optimization, variable stiffness

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Authors: Chanh Nghia Nguyen, Yu Kurokawa, Hirotsugu Inoue

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The surface roughness is an important parameter for evaluating the quality of material surfaces since it affects functions and performance of industrial components. Although stylus and optical techniques are commonly used for measuring the surface roughness, they are applicable only to accessible surfaces. In practice, surface roughness measurement from the back side is sometimes demanded, for example, in inspection of safety-critical parts such as inner surface of pipes. However, little attention has been paid to the measurement of back surface roughness so far. Since back surface is usually inaccessible by stylus or optical techniques, ultrasonic technique is one of the most effective among others. In this research, an ultrasonic pulse-echo technique is considered for evaluating the pitch and the height of back surface having periodic triangular profile as a very first step. The pitch of the surface profile is measured by applying the diffraction grating theory for oblique incidence; then the height is evaluated by numerical analysis based on the Kirchhoff theory for normal incidence. The validity of the proposed method was verified by both numerical simulation and experiment. It was confirmed that the pitch is accurately measured in most cases. The height was also evaluated with good accuracy when it is smaller than a half of the pitch because of the approximation in the Kirchhoff theory.

Keywords: back side, inaccessible surface, periodic roughness, pulse-echo technique, ultrasonic NDE

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Authors: Md. Khayrul Bashar, Md. Saiful Islam, Kimiko Yamashita, Yano Midori

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Despite having some progress in human authentication, conventional biometrics (e.g., facial features, fingerprints, retinal scans, gait, voice patterns) are not robust against falsification because they are neither confidential nor secret to an individual. As a non-invasive tool, electrocardiogram (ECG) has recently shown a great potential in human recognition due to its unique rhythms characterizing the variability of human heart structures (chest geometry, sizes, and positions). Moreover, ECG has a real-time vitality characteristic that signifies the live signs, which ensure legitimate individual to be identified. However, the detection accuracy of the current ECG-based methods is not sufficient due to a high variability of the individual’s heartbeats at a different instance of time. These variations may occur due to muscle flexure, the change of mental or emotional states, and the change of sensor positions or long-term baseline shift during the recording of ECG signal. In this study, a new method is proposed for human identification, which is based on the extraction of the local roughness of ECG heartbeat signals. First ECG signal is preprocessed using a second order band-pass Butterworth filter having cut-off frequencies of 0.00025 and 0.04. A number of local binary patterns are then extracted by applying a moving neighborhood window along the ECG signal. At each instant of the ECG signal, the pattern is formed by comparing the ECG intensities at neighboring time points with the central intensity in the moving window. Then, binary weights are multiplied with the pattern to come up with the local roughness description of the signal. Finally, histograms are constructed that describe the heartbeat signals of individual subjects in the database. One advantage of the proposed feature is that it does not depend on the accuracy of detecting QRS complex, unlike the conventional methods. Supervised recognition methods are then designed using minimum distance to mean and Bayesian classifiers to identify authentic human subjects. An experiment with sixty (60) ECG signals from sixty adult subjects from National Metrology Institute of Germany (NMIG) - PTB database, showed that the proposed new method is promising compared to a conventional interval and amplitude feature-based method.

Keywords: human identification, ECG biometrics, local roughness patterns, supervised classification

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Authors: Nazia Shehzad

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An icebreaker is a facilitation exercise intended to help a group to begin the process of forming themselves into a team. Icebreakers are commonly presented as a game to ‘warm up’ the group by helping the members to get to know each other. They often focus on sharing personal information such as names, hobbies, etc. Challenging icebreakers also have the ability to allow a group to be better prepared to complete its assigned tasks. For example, if the team's objective is to redesign a business process such as Accounts Payable, the icebreaker activity might take the team through a process analysis. The analysis could include the identification of failure points, challenging assumptions, and development of new solutions — all in a simpler and ‘safer’ setting where the team can practice the group dynamics which they will use to solve the assigned problem. Icebreakers help establish a positive environment and provide an opportunity for students to get to know one another and the instructor. Both are critical to the retention and success of students. There are a number of benefits of using ice-breakers activities in the classroom. It reduces both student and instructor anxiety prior to introducing the course, fosters in a powerful way both student-student and faculty-student interactions. It creates an environment where the learner is expected to participate and the instructor is willing to listen, actively engage students from the onset. It conveys the message that the instructor cares about getting to know the students and makes it easier for students to form relationships early in the semester so they can work together both in and out of class.

Keywords: actively engages students, facilitation exercise, faculty- student interactions, group dynamics, warm up

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Authors: Ali A. Al-Jazaairry, Tahsin T. Sabbagh

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Presence of cavities in soil predictably induces ground deformation and changes in soil stress, which might influence adjacent existing pile foundations, though the effect of twin cavities on a nearby pile needs to be understood. This research is an attempt to identify the behaviour of piles subjected to axial load and embedded in cavitied clayey soil. A series of finite element modelling were conducted to investigate the performance of piled foundation located in such soils. The validity of the numerical simulation was evaluated by comparing it with available field test and alternative analytical model. The study involved many parameters such as twin cavities size, depth, spacing between cavities, and eccentricity of cavities from the pile axis on the pile performance subjected to axial load. The study involved many cases; in each case, a critical value has been found in which cavities’ presence has shown minimum impact on the behaviour of pile. Load-displacement relationships of the affecting parameters on the pile behaviour were presented to provide helpful information for designing piled foundation situated near twin underground cavities. It was concluded that the presence of the cavities within the soil mass reduces the ultimate capacity of pile. This reduction differs according to the size and location of the cavity.

Keywords: axial load, clay, finite element, pile, twin cavities, ultimate capacity

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Authors: Xize Dai, Jian Hao, Claus Leth Bak, Gian Carlo Montanari, Huai Wang

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Printed Circuit Board (PCB) is a critical component applicable to power electronics systems, especially for high-voltage applications involving several high-voltage and high-frequency SiC/GaN devices. The insulation system of PCB is facing more challenges from high-voltage and high-frequency stress that can alter the dielectric properties. Dielectric properties of the PCB insulation system also determine the electrical field distribution that correlates with intrinsic and extrinsic aging mechanisms. Hence, investigating the dielectric properties in the frequency domain of the PCB insulation system is a must. The paper presents the frequency-dependent, temperature-dependent, and voltage-dependent dielectric properties, permittivity, conductivity, and dielectric loss tangents of PCB insulation systems. The dielectric properties mechanisms associated with frequency, temperature, and voltage are revealed from the design perspective. It can be concluded that the dielectric properties of PCB in the frequency domain show a strong dependence on voltage, frequency, and temperature. The voltage-, frequency-, and temperature-dependent dielectric properties are associated with intrinsic conduction behavior and polarization patterns from the perspective of dielectric theory. The results may provide some reference for the PCB insulation system design in high voltage, high frequency, and high-temperature power electronics applications.

Keywords: electrical insulation system, dielectric properties, high voltage and frequency, printed circuit board

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Authors: Bethany Wood

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The world pandemic led to a change in the way social media was used by audiences, with young people spending more hours on the platform due to lockdown. Reports by Ofcom have demonstrated that the internet is the second most popular platform for accessing news after television in the UK with social media and the internet ranked as the most popular platform to access news for those aged between 16-24. These statistics are unsurprising considering that at the time of writing, 98 percent of Generation Z (Gen Z) owned a smartphone and the subsequent ease and accessibility of social media. Technology is constantly developing and with this, its importance is becoming more prevalent with each generation: the Baby Boomers (1946-1964) consider it something useful whereas millennials (1981-1997) believe it a necessity for day to day living. Gen Z, otherwise known as the digital native, have grown up with this technology at their fingertips and social media is a norm. It helps form their identity, their affiliations and opens gateways for them to engage with news in a new way. It is a common misconception that Gen Z do not consume news, they are simply doing so in a different way to their predecessors. Using a sample of 800 18-20 year olds whilst utilising Generational theory, Actor Network Theory and the Social Shaping of Technology, this research provides a critical analyse regarding how Gen Z’s news consumption and engagement habits are developing along with technology to sculpture the future format of news and its distribution. From that perspective, allied with the empirical approach, it is possible to provide research orientated advice for the industry and even help to redefine traditional concepts of journalism.

Keywords: journalism, generation z, digital, social media

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Authors: Ljiljana Seric, Vladimir Divic, Marin Bugaric

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This paper presents methodology for spatial analysis of GIS data that is used for assessing the microlocation risk index from potential damages of high winds. The analysis is performed on freely available GIS data comprising information about wind load, terrain cover and topography of the area. The methodology utilizes the legislation of Eurocode norms for determination of wind load of buildings and constructions. The core of the methodology is adoption of the wind load parameters related to location on geographical spatial grid. Presented work is a part of the Wind Risk Project, supported by the European Commission under the Civil Protection Financial Instrument of the European Union (ECHO). The partners involved in Wind Risk project performed Wind Risk assessment and proposed action plan for three European countries – Slovenia, Croatia and Germany. The proposed method is implemented in GRASS GIS open source GIS software and demonstrated for Case study area of wider area of Split, Croatia. Obtained Wind Risk Index is visualized and correlated with critical infrastructures like buildings, roads and power lines. The results show good correlation between high Wind Risk Index with recent incidents related to wind.

Keywords: Eurocode norms, GIS, spatial analysis, wind distribution, wind risk

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Authors: Rim Baroudi

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The notion of the context-induced metaphors refers to the role of different contextual aspects (socio-cultural, linguistic, bodily-physical, and ideological) in affecting metaphor production. This has not been investigated in visual discourse. This paper intends to extend the focus of this research interest to study context-induced metaphors in newspapers’ cartoons. It seeks to account for different contextual variables influencing the production of metaphors in cartoons placing special focus on the ideological variable. The aim is to demonstrate how different contextual aspects are conditioned by the ideological variable. The study applied critical metaphor approach to analyse contextual variables shaping the conceptualization of ‘the Islamic State’ in the cartoons of 3 newspapers (Al-Ryadh newspaper, Tehran Times, and The New York Times). Findings have revealed the decisive role of the ideological context in conditioning and priming the rest of contextual variables in the conceptualisation of ‘the Islamic State’ in political cartoons of the three newspapers. These findings bear special importance to the study of bodily-physical and socio-cultural variables inducing and shaping political cognition in political cartoons in a way consistent with the ideological framework within which newspapers operate.

Keywords: context-induced metaphors, ideological context, the Islamic State, political cartoons

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Authors: Amrutha Venugopal, Rabee Rustum

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In spite of huge investments and the vital role infrastructure plays in the economy of UAE, the country has not yet developed an assessment scheme to measure the sustainability of infrastructure projects/development. The aim of this study was to develop a sustainability rating system for infrastructure projects in UAE using weighted indicator scoring. The identification of the list of 66 indicators was done by content analysis. The sources of content analysis were from government guidelines, research literature and sustainability rating system for infrastructure projects namely BCA Greenmark for Infrastructure (Singapore), ISCA (Australia) and Envision (USA). These indicators were shortlisted based on their relevance in the UAE. A mixture of qualitative and quantitative research methods is utilized to find the weightage to be applied to the indicators and to find suggestive measures to improve infrastructure sustainability in this region. Interviews and surveys were conducted with a good mix of experts from the industry. The data collected from the interviews were collated to provide suggestive measures for improving infrastructure sustainability. The collected survey data were analyzed using statistical analysis techniques to find the indicator weighing. The indicators were shortlisted by 75% to minimize the effort and investment into the process. The weighing of the deleted indicators was distributed among the critical clusters identified by Pareto analysis. Finally a simple Microsoft Excel tool was developed as the rating tool by using the calculated weighing for the indicators.

Keywords: infrastructure, rating system, suggestive measures, sustainability, UAE

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Li-Ju Chen, Hsiang-Lin Chan, Hsin-Yi Kathy Cheng, Hui-Ju Chen

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Stereotype behavior is one of the maladaptive syndromes of the individuals with autism. Most of the previous researches focused on the stereotype behavior with stimulating type, while less on the stereotype behavior about cognition (This research names it cognitive stereotype behavior; CSB). This research explored CSB and the rationality to explain CSB with imprinting phenomenon. After excluding the samples without CSB described, the data that came from 271 individuals with autism were recruited and analyzed with quantitative and qualitative analyses. This research discovers that : (1) Most of the individuals with autism originally came out CSB at 3 years old and more than a half of them appeared before 4 years old; The average age which firstly came out CSB was 6.10 years old, the average time insisting or ossifying CSB was 31.71 minutes each time and the average longest time which they last was 358.35 minutes (5.97 hours). (2) CSB demonstrates various aspects, this research classified them into 4 fields with 26 categories. They were categorized into sudden CSB or habitual CSB by imprinting performance. (3) Most of the autism commented that their CSBs were not necessary but they could not control them well. One-third of them appeared CSB suddenly and the first occurrence accompanied a strong emotional or behavioral response. (4) Whether respondent is the person with autism himself/herself or not was the critical element: on the awareness of the severity degree, disturbance degree, and the emotional /behavioral intensity at the first-time CSB happened. This study concludes imprinting could reasonably explain the phenomenon CSB forms. There are implications leading the individuals with autism and their family to develop coping strategies to promote individuals with autism having a better learning accomplishment and life quality in their future.

Keywords: autism, cognitive stereotype behavior, constructivism, imprinting, stereotype

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Authors: Nooshin Salari, Viliam Makis, Jane Doe

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This paper presents a maintenance policy for a system consisting of two units. Unit 1 is gradually deteriorating and is subject to soft failure. Unit 2 has a general lifetime distribution and is subject to hard failure. Condition of unit 1 of the system is monitored periodically and it is considered as failed when its deterioration level reaches or exceeds a critical level N. At the failure time of unit 2 system is considered as failed, and unit 2 will be correctively replaced by the next inspection epoch. Unit 1 or 2 are preventively replaced when deterioration level of unit 1 or age of unit 2 exceeds the related preventive maintenance (PM) levels. At the time of corrective or preventive replacement of unit 2, there is an opportunity to replace unit 1 if its deterioration level reaches the opportunistic maintenance (OM) level. If unit 2 fails in an inspection interval, system stops operating although unit 1 has not failed. A mathematical model is derived to find the preventive and opportunistic replacement levels for unit 1 and preventive replacement age for unit 2, that minimize the long run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. Numerical example is provided to illustrate the performance of the proposed model and the comparison of the proposed model with an optimal policy without opportunistic maintenance level for unit 1 is carried out.

Keywords: condition-based maintenance, opportunistic maintenance, preventive maintenance, two-unit system

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Authors: Olivia Martina Dalla Torre

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The aim of this paper is to describe and analyse some urban writings that emerge in politically disputed areas, namely the Occupied Palestinian Territories, and more specifically in Deheishe refugee camp. These graffiti are visible on the walls of houses, all around the camp, and they convey messages of protest but also of hope or claim about the complex political situation in the occupied territories. These graffiti can be then interpreted as political and politicized semiotic resources. In this paper, after having introduced the political situation of the Palestinian Territories in a historical perspective, we will question a specific dimension of these writings, i.e., their multilingual and ideological aspect. To do this, we will focus on ethnographic fieldwork on Deheishe refugee camp and we will draw on the theoretical framework of the critical communication studies which assert that language practices are not neutral and that they need to be understood through the lens of the historical context of production, crossing space and time. By analysing the relationship between the discursive constructions of the messages and the languages used, we will point out some of the possible reasons and functions of the presence of these multilingual discursive productions. We will show that if, on the one hand, these graffiti confirm the huge presence of Western actors in the region, on the other hand, they attest the presence of an international movement against the Israeli occupation and against other struggles as well. Concluding, we will argue that multilingualism certainly represents a diversification of the linguistic landscape and that it gives a transnational and political dimension to the graffiti.

Keywords: communication, graffiti, multilingualism, Palestine, transnationalism

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Authors: Zahra Mehrabbeygi

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This research is opted to analyze and survey discourse variety and news image-making in western media regarding the news coverage of the Russian army intrusion into Ukraine. This research will be done on the news coverage of Ukraine in a period from February 2022 to May 2022 in five western media, "BBC, CBS, NBC, Al Jazeera, and Telegraph." This research attempts to discover some facts about the news policies of the five western news agencies during the circumstances of the Ukraine-Russia war. Critical theories in the news, such as Framing, Media Imperialism of News, Image Making, Discourse, and Ideology, were applied to achieve this goal. The research methodology uses Van Dijk's discourse exploration method based on discourse analysis. The research's statistical population is related to all the news about racial discrimination during the mentioned period. After a statistical population survey with Targeted Sampling, the researcher randomly selected ten news cases for exploration. The research findings show that the western media have similarities in their texts via lexical items, polarization, citations, persons, and institutions. The research findings also imply pre-suppositions, connotations, and components of consensus agreement and underlying predicates in the outset, middle, and end events. The reaction of some western media not only shows their bewilderment but also exposes their prejudices rooted in racism.

Keywords: news discourse analysis, western media, racial discrimination, Ukraine-Russia war

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Authors: Aditya Pal, S. Z. S. Tabish, Kumar Neeraj Jha

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In the construction industry, engineering procurement and construction (EPC) projects are becoming increasingly prevalent; they provide clients with benefits such as decreased workload, streamlined execution, and a singular point of accountability. EPC projects entail round-the-clock operations, which calls for an analysis of the variables that impact productivity during nocturnal hours. The current body of research on the distinctions between daytime and nighttime construction lacks a comprehensive examination of nocturnal attributes. The objective of this research is to ascertain the critical factors that influence the productivity of nighttime construction by conducting site investigations and reviewing relevant literature. The influence of factors such as illumination conditions, equipment deployment, quality procedures, and government regulations on productivity is subject to careful examination. The studies rank the significance of these factors in accordance with the relative importance index (RII) and entropy weighted method (EWM). The primary determinants identified in the study are temperature (RII: 0.8444), weather conditions (RII: 0.8222), and material and apparatus maintenance (RII: 0.8222). The findings function as recommendations for project managers and EPC contractors to reduce setbacks and increase efficiency. By comparing the outcomes of EWM and RII, the most effective approach to resolving the most crucial characteristics is achieved.

Keywords: productivity, nighttime work, statistical methods, construction, entropy weighted method, relative importance indexing

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Authors: Alicia Yanadira Nava Fuentes, Ilse Cervantes Camacho, Amadeo José Argüelles Cruz, Ana María Balboa Verduzco

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Augmented reality promises being present in future driving, with its immersive technology let to show directions and maps to identify important places indicating with graphic elements when the car driver requires the information. On the other side, driving is considered a multitasking activity and, for some people, a complex activity where different situations commonly occur that require the immediate attention of the car driver to make decisions that contribute to avoid accidents; therefore, the main aim of the project is the instrumentation of a platform with biometric sensors that allows evaluating the performance in driving vehicles with the influence of augmented reality devices to detect the level of attention in drivers, since it is important to know the effect that it produces. In this study, the physiological sensors EPOC X (EEG), ECG06 PRO and EMG Myoware are joined in the driving test platform with a Logitech G29 steering wheel and the simulation software City Car Driving in which the level of traffic can be controlled, as well as the number of pedestrians that exist within the simulation obtaining a driver interaction in real mode and through a MSP430 microcontroller achieves the acquisition of data for storage. The sensors bring a continuous analog signal in time that needs signal conditioning, at this point, a signal amplifier is incorporated due to the acquired signals having a sensitive range of 1.25 mm/mV, also filtering that consists in eliminating the frequency bands of the signal in order to be interpretative and without noise to convert it from an analog signal into a digital signal to analyze the physiological signals of the drivers, these values are stored in a database. Based on this compilation, we work on the extraction of signal features and implement K-NN (k-nearest neighbor) classification methods and decision trees (unsupervised learning) that enable the study of data for the identification of patterns and determine by classification methods different effects of augmented reality on drivers. The expected results of this project include are a test platform instrumented with biometric sensors for data acquisition during driving and a database with the required variables to determine the effect caused by augmented reality on people in simulated driving.

Keywords: augmented reality, driving, physiological signals, test platform

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Authors: Maitreyee Datta

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In Anātmalaksana Sutra, Buddha talks about the importance of anattā (no-self). This notion of no-self is a critical response towards the Brahmanical tradition of classical India in which self has been taken to be eternal. Though self is taken to be eternal, ‘I’ refer to Person who is the self as determined by non-eternal body. Buddha raises questions regarding the possibility of the association between eternal self and non-eternal body. According to him, such an association is not possible. Thus, instead of an eternal self and its association with the non-eternal body, he speaks about association among five different non-eternal parts (skandhas). He holds that ‘I’ refers to Person, but this Person is not eternal self as determined by the non-eternal body. It is the combination of five different skandhas each of which is non-eternal. So according to Buddha, there is no eternal self which in association with non-eternal body is referred to as ‘I,’ but ‘I’ is a convenient designator which designates the combination of five non-eternal skandhas. If ‘I’ is taken to refer the combination of five non-eternal skandhas, then the problematic of the association between eternal self (attā) and non-eternal body will not be there. The realization that ‘I’ does not refer to any eternal self as determined by non-eternal body, but instead refer to the combination of five non-eternal skandhas leads to the cessation of suffering (duhkkha). The root of suffering lies in craving for something or the other. Thus, as soon as one realizes that the person is not constituted of any eternal self but is constituted of non-eternal skandhas, his desire to acquire and possess will be stopped. Thus, in the whole conceptual framework of Buddhist philosophy, anattā occupies a pivotal role the realization of which is admitted to be the cause of the cessation of suffering. In the present paper, an effort will be made to analyse this notion of anattā to show how the realization of the truth that person is a combination of five skandhas each of which is non-eternal helps an individual to get rid of the bondage. If eternal self is to be admitted, then there always remains the problem of connecting the eternal self with the non-eternal body, because this connection only gives rise to the notion of person in such framework.

Keywords: anatta, atta, duhkkha, skandha

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Authors: Anderson Rocha-Buelvas, Jaqueline Mena Huertas, Edith Burbano Rosero, Arsenio Hidalgo Troya, Mauricio Casas Cruz

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COVID-19 is a disruptive pandemic for the public health and economic system of whole countries, including Colombia. Nariño Department is the southwest of the country and draws attention to being on the border with Ecuador, constantly facing demographic transition affecting infections between countries. In Nariño, the early routine diagnosis of SARS-CoV-2, which can be handled at BSL-2, has affected the transmission dynamics of COVID-19. However, new emerging and re-emerging viruses with biological flexibility classified as a Risk Group 3 agent can take advantage of epidemiological opportunities, generating the need to increase clinical diagnosis, mainly in border regions between countries. The overall objective of this project was to assure the quality of the analytical process in the diagnosis of high biological risk pathogens in Nariño by building a laboratory that includes biosafety level (BSL)-2 and (BSL)-3 containment zones. The delimitation of zones was carried out according to the Verification Tool of the National Health Institute of Colombia and following the standard requirements for the competence of testing and calibration laboratories of the International Organization for Standardization. This is achieved by harmonization of methods and equipment for effective and durable diagnostics of the large-scale spread of highly pathogenic microorganisms, employing negative-pressure containment systems and UV Systems in accordance with a finely controlled electrical system and PCR systems as new diagnostic tools. That increases laboratory capacity. Protection in BSL-3 zones will separate the handling of potentially infectious aerosols within the laboratory from the community and the environment. It will also allow the handling and inactivation of samples with suspected pathogens and the extraction of molecular material from them, allowing research with pathogens with high risks, such as SARS-CoV-2, Influenza, and syncytial virus, and malaria, among others. The diagnosis of these pathogens will be articulated across the spectrum of basic, applied, and translational research that could receive about 60 daily samples. It is expected that this project will be articulated with the health policies of neighboring countries to increase research capacity.

Keywords: medical laboratory science, SARS-CoV-2, public health surveillance, Colombia

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Authors: T. Sarat Chandra, M. Maneesh Kumar, S. N. Mudliar, V. S. Chauhan, S. Mukherji, R. Sarada

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The life cycle assessment (LCA) of biodiesel production from freshwater microalgae Scenedesmus dimorphus cultivated in open raceway pond is performed. Various scenarios for biodiesel production were simulated using primary and secondary data. The parameters varied in the modelled scenarios were related to biomass productivity, mode of culture mixing and type of energy source. The process steps included algae cultivation in open raceway ponds, harvesting by chemical flocculation, dewatering by mechanical drying option (MDO) followed by extraction, reaction and purification. Anaerobic digestion of defatted algal biomass (DAB) for biogas generation is considered as a co-product allocation and the energy derived from DAB was thereby used in the upstream of the process. The scenarios were analysed for energy demand, emissions and environmental impacts within the boundary conditions grounded on "cradle to gate" inventory. Across all the Scenarios, cultivation via raceway pond was observed to be energy intensive process. The mode of culture mixing and biomass productivity determined the energy requirements of the cultivation step. Emissions to Freshwater were found to be maximum contributing to 93-97% of total emissions in all the scenarios. Global warming potential (GWP) was the found to be major environmental impact accounting to about 99% of total environmental impacts in all the modelled scenarios. It was noticed that overall emissions and impacts were directly related to energy demand and an inverse relationship was observed with biomass productivity. The geographic location of an energy source affected the environmental impact of a given process. The integration of defatted algal remnants derived electricity with the cultivation system resulted in a 2% reduction in overall energy demand. Direct biogas generation from microalgae post harvesting is also analysed. Energy surplus was observed after using part of the energy in upstream for biomass production. Results suggest biogas production from microalgae post harvesting as an environmentally viable and sustainable option compared to biodiesel production.

Keywords: biomass productivity, energy demand, energy source, Lifecycle Assessment (LCA), microalgae, open raceway pond

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Authors: Sofia Horjales, Florencia Palma

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Our society is currently experiencing a profound transformation, demanding a proactive response from governmental bodies and higher education institutions to empower the next generation as catalysts for change. Environmental sustainability is rooted in the critical need to maintain the equilibrium and integrity of natural ecosystems, ensuring the preservation of precious natural resources and biodiversity for the benefit of both present and future generations. It is an essential cornerstone of sustainable development, complementing social and economic sustainability. In this evolving landscape, active methodologies take a central role, aligning perfectly with the principles of the 2030 Agenda for Sustainable Development and emerging as a pivotal element of teacher education. The emphasis on active learning methods has been driven by the urgent need to nurture sustainability and instill social responsibility in our future leaders. The Universidad Tecnológica of Uruguay (UTEC) is a public, technologically-oriented institution established in 2012. UTEC is dedicated to decentralization, expanding access to higher education throughout Uruguay, and promoting inclusive social development. Operating through Regional Technological Institutes (ITRs) and associated centers spread across the country, UTEC faces the challenge of remote student populations. To address this, UTEC utilizes e-learning for equal opportunities, self-regulated learning, and digital skills development, enhancing communication among students, teachers, and peers through virtual classrooms. The Interdisciplinary Continuing Education Program is part of the Innovation and Entrepreneurship Department of UTEC. The main goal is to strengthen innovation skills through a transversal and multidisciplinary approach. Within this Program, we have developed a Case of Study and Project-Based Learning Virtual Course designed for university students and open to the broader UTEC community. The primary aim of this course is to establish a strong foundation for comprehending and addressing environmental sustainability issues from an interdisciplinary perspective. Upon completing the course, we expect students not only to understand the intricate interactions between social and ecosystem environments but also to utilize their knowledge and innovation skills to develop projects that offer enhancements or solutions to real-world challenges. Our course design centers on innovative learning experiences, rooted in active methodologies. We explore the intersection of these methods with sustainability and social responsibility in the education of university students. A paramount focus lies in gathering student feedback, empowering them to autonomously generate ideas with guidance from instructors, and even defining their own project topics. This approach underscores that when students are genuinely engaged in subjects of their choice, they not only acquire the necessary knowledge and skills but also develop essential attributes like effective communication, critical thinking, and problem-solving abilities. These qualities will benefit them throughout their lifelong learning journey. We are convinced that education serves as the conduit to merge knowledge and cultivate interdisciplinary collaboration, igniting awareness and instigating action for environmental sustainability. While systemic changes are undoubtedly essential for society and the economy, we are making significant progress by shaping perspectives and sparking small, everyday actions within the UTEC community. This approach empowers our students to become engaged global citizens, actively contributing to the creation of a more sustainable future.

Keywords: active learning, environmental education, project-based learning, soft skills development

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Authors: Ahmed Auda, Manjree Agarwala, Giles Hardya, Yonglin Rena

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Botrytis cinerea is a major pest for many plants. It can attack a wide range of plant parts. It can attack buds, flowers, and leaves, stems, and fruit. However, B. cinerea can be mixed with other diseases that cause the same damage. There are many species of botrytis and more than one different strains of each. Botrytis might infect the foliage of nursery stock stored through winter in damp conditions. There are no known resistant plants. Botrytis must have nutrients or food source before it infests the plant. Nutrients leaking from wounded plant parts or dying tissue like old flower petals give the required nutrients. From this food, the fungus becomes more attackers and invades healthy tissue. Dark to light brown rot forms in the ill tissue. High humidity conditions support the growth of this fungus. However, we suppose that selection pressure can act on the morphological and neurophysiologic filter properties of the receiver and on both the biochemical and the physiological regulation of the signal. Communication is implied when signal and receiver evolves toward more and more specific matching, culminating. In other hand, receivers respond to portions of a body odor bouquet which is released to the environment not as an (intentional) signal but as an unavoidable consequence of metabolic activity or tissue damage. Each year Botrytis species can cause considerable economic losses to plant crops. Even with the application of strict quarantine and control measures, these fungi can still find their way into crops and cause the imposition of onerous restrictions on exports. Blueberry fruit mould caused by a fungal infection usually results in major losses during post-harvest storage. Therefore, the management of infection in early stages of disease development is necessary to minimize losses. The overall purpose of this study will develop sensitive, cheap, quick and robust diagnostic techniques for the detection of B. cinerea in blueberry. The specific aim was designed to investigate the performance of volatile organic compounds (VOCs) in the detection and discrimination of blueberry fruits infected by fungal pathogens with an emphasis on Botrytis in the early storage stage of post-harvest.

Keywords: botrytis cinerea, blueberry, GC/MS, VOCs

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Authors: Golyasamin Khanehzaei, Mohd. Bakri Ishak, Ahmad Makmom Hj Abdullah, Latifah Abd Manaf

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Abstract—Management of clinical waste is a critical problem worldwide. Immediate attention is required to manage the clinical waste in an appropriate way in newly developing economy country such as Malaysia. The increasing amount of clinical waste generated is resulted from rapid urbanization and growing number of private health care facilities in developing countries such as Malaysia. In order to develop a sensible clinical waste management system and improvement of the management, information on factors affecting clinical waste generation has the crucial role. This paper is the study of management characteristics of clinical waste and the level of efficiency of clinical waste management systems operating in private clinics located in Selangor, Malaysia. Are they following the proper international standards? By taking all of this in consideration the aim of this paper is to identify and discuss the current trend, current challenges and also the present opportunities among the challenges of clinical waste management in private clinics of Selangor, Malaysia. The SWOT analysis was characterized for the evaluation of strengths, weaknesses, opportunities and threats. The methodology for this study was constituted of direct observation, Informal interviews, Conducting SWOT analysis, conduction of one sustainability dimensions analysis and application. The results show that clinical waste management in private clinics is far from an ideal model.

Keywords: clinical waste, SWOT analysis, Selangor, Malaysia

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Authors: Yina F. Muñoz, Alexander Paz, Hanns De La Fuente-Mella, Joaquin V. Fariña, Guilherme M. Sales

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The primary approach for estimating bridge deterioration uses Markov-chain models and regression analysis. Traditional Markov models have problems in estimating the required transition probabilities when a small sample size is used. Often, reliable bridge data have not been taken over large periods, thus large data sets may not be available. This study presents an important change to the traditional approach by using the Small Data Method to estimate transition probabilities. The results illustrate that the Small Data Method and traditional approach both provide similar estimates; however, the former method provides results that are more conservative. That is, Small Data Method provided slightly lower than expected bridge condition ratings compared with the traditional approach. Considering that bridges are critical infrastructures, the Small Data Method, which uses more information and provides more conservative estimates, may be more appropriate when the available sample size is small. In addition, regression analysis was used to calculate bridge deterioration. Condition ratings were determined for bridge groups, and the best regression model was selected for each group. The results obtained were very similar to those obtained when using Markov chains; however, it is desirable to use more data for better results.

Keywords: concrete bridges, deterioration, Markov chains, probability matrix

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Authors: Chenghao Ma

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This paper mainly examines and compares the primary revenue sources in the professional sports, intercollegiate sports, and sporting goods industries in the U.S. In the professional team sport, revenues may come from different resources, including broadcasting rights, ticket sales, corporate partnerships, naming rights, licensed merchandise, luxury suites, club seating, ancillary activities, and transfer fees. Many universities use university budgets and student fees to cover the cost of collegiate athletics. Other sources of revenue include ticket sales, broadcast rights, concessions, corporate partnerships, cash contributions from alumni, and others. Revenues in the sporting goods industry are very different compared with professional sports teams and collegiate athletics. Sporting goods companies mainly sell a line of products and equipment to generate revenue. Revenues are critical for sports organizations, including professional sports teams, intercollegiate athletics, and sporting goods companies. There are similarities and differences among these areas. Sports managers are looking for new ways to generate revenues, and there are many changes of sources because of the development of the internet and technology. Compared with intercollegiate athletics, professional sport and sporting goods companies will create more revenue opportunities globally.

Keywords: revenue sources, professional sports, intercollegiate athletics, sporting goods industry

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Authors: Juan Manuel Martinez Alvarez, Michele Chiumenti

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This work explores the benefit of the thermo-metallurgical simulation to tackle the Wire Laser Additive Manufacturing (WLAM) of low-carbon steel components. The Finite Element Analysis is calibrated by process monitoring via thermal imaging and thermocouples measurements, to study the complex thermo-metallurgical behavior inherent to the WLAM process of low carbon steel parts.A critical aspect is the analysis of the heterogeneity in the resulting microstructure. This heterogeneity depends on both the thermal history and the residual stresses experienced during the WLAM process. Because of low carbon grades are highly sensitive to quenching, a high-gradient microstructure often arises due to the layer-by-layer metal deposition in WLAM. The different phases have been identified by scanning electron microscope. A clear influence of the heterogeneities on the final mechanical performance has been established by the subsequent mechanical characterization. The thermo-metallurgical analysis has been used to determine the actual thermal history and the corresponding thermal gradients during the printing process. The correlation between the thermos-mechanical evolution, the printing parameters and scanning sequence has been established. Therefore, an enhanced printing strategy, including optimized process window has been used to minimize the microstructure heterogeneity at ArcelorMittal.

Keywords: additive manufacturing, numerical simulation, metallurgy, steel

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Authors: Tricia Agocs, Debra Langan, Carrie B. Sanders

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Studies of the challenges faced by women in policing have paid little attention to the specific experiences of Policewomen who are mothers. Guided by critical theorizing on the gendered nature of the police culture and domestic labor, 16 police officer mothers in Ontario, Canada, were interviewed. Our qualitative analyses explore their experiences of the “lion’s share” of domestic labor; the organizational, cultural, and operational features of policing; and the challenges of child care, and examine how these combine to foster particular stresses. In contrast to intensive mothering approaches that rely on the advice of external experts, our participants work to protect children by carefully constructing stories and asking questions that are based on their own on-the-job experiences with dangerous and/or abhorrent situations. As such, they engage in danger-protection parenting practices to prevent their children from becoming victims or offenders. Our research extends the theorizing on intensive/extensive mothering practices, builds on the scholarship on policing, and adds to the literature on women in nonstandard occupations. This sociological analysis of police mothers’ experiences and practices underscores the importance of understanding and working to change the social contexts, at work and at home, that compromise the well-being of police mothers and other emergency-response workers.

Keywords: policewomen, mothers, parenting, danger, qualitative research

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Authors: Connor Dunlop, Bassim Abbassi, Richard G. Zytner

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Life cycle assessment (LCA) is a powerful tool established by the International Organization for Standardization (ISO) that can be used to assess the environmental impacts of a product or process from cradle to grave. Many studies utilize the LCA methodology within the site remediation field to compare various decontamination methods, including bioremediation, soil vapor extraction or excavation, and off-site disposal. However, with the authors' best knowledge, limited information is available in the literature on a sustainability tool that could be used to help with the selection of the optimal remediation technology. This tool, based on the LCA methodology, would consider site conditions like environmental, economic, and social impacts. Accordingly, this project was undertaken to develop a tool to assist with the selection of optimal sustainable technology. Developing a proper tool requires a large amount of data. As such, data was collected from previous LCA studies looking at site remediation technologies. This step identified knowledge gaps or limitations within project data. Next, utilizing the data obtained from the literature review and other organizations, an extensive LCA study is being completed following the ISO 14040 requirements. Initial technologies being compared include bioremediation, excavation with off-site disposal, and a no-remediation option for a generic gasoline-contaminated site. To complete the LCA study, the modelling software SimaPro is being utilized. A sensitivity analysis of the LCA results will also be incorporated to evaluate the impact on the overall results. Finally, the economic and social impacts associated with each option will then be reviewed to understand how they fluctuate at different sites. All the results will then be summarized, and an interactive tool using Excel will be developed to help select the best sustainable site remediation technology. Preliminary LCA results show improved sustainability for the decontamination of a gasoline-contaminated site for each technology compared to the no-remediation option. Sensitivity analyses are now being completed on on-site parameters to determine how the environmental impacts fluctuate at other contaminated gasoline locations as the parameters vary, including soil type and transportation distances. Additionally, the social improvements and overall economic costs associated with each technology are being reviewed. Utilizing these results, the sustainability tool created to assist in the selection of the overall best option will be refined.

Keywords: life cycle assessment, site remediation, sustainability tool, contaminated sites

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