Search results for: space domain analysis

Authors: Mei-Jie Xu, Yang Zhong

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Based on the symplectic geometry method, the theory of Hamilton system can be applied in the analysis of problem solved using the theory of elasticity and in the solution of elliptic partial differential equations. With this technique, this paper derives the theoretical solution for a thick rectangular plate with four free edges supported on a Winkler foundation by variable separation method. In this method, the governing equation of thick plate was first transformed into state equations in the Hamilton space. The theoretical solution of this problem was next obtained by applying the method of variable separation based on the Hamilton system. Compared with traditional theoretical solutions for rectangular plates, this method has the advantage of not having to assume the form of deflection functions in the solution process. Numerical examples are presented to verify the validity of the proposed solution method.

Keywords: symplectic geometry method, Winkler foundation, thick rectangular plate, variable separation method, Hamilton system

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Authors: Petra Hypšová, Martin Seitl

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One of the challenges of forensic psychology is to detect deception during a face-to-face interview. In addition to the classical approaches of monitoring the utterance and its components, detection is also sought by observing behavioral and physiological changes that occur as a result of the increased emotional and cognitive load caused by the production of distorted information. Typical are changes in facial temperature, eye movements and their fixation, pupil dilation, emotional micro-expression, heart rate and its variability. Expanding technological capabilities have opened the space to detect these psychophysiological changes and behavioral manifestations through non-contact technologies that do not interfere with face-to-face interaction. Non-contact deception detection methodology is still in development, and there is a lack of studies that combine multiple non-contact technologies to investigate their accuracy, as well as studies that show how different types of lies produced by different interviewers affect physiological and behavioral changes. The main objective of this study is to apply a specific non-contact technology for deception detection. The next objective is to investigate scenarios in which non-contact deception detection is possible. A series of psychophysiological experiments using infrared thermal imaging, eye tracking and behavioral analysis with FaceReader 9.0 software was used to achieve our goals. In the laboratory experiment, 16 adults (12 women, 4 men) between 18 and 35 years of age (SD = 4.42) were instructed to produce alternating prepared and spontaneous truths and lies. The baseline of each proband was also measured, and its results were compared to the experimental conditions. Because the personality of the examiner (particularly gender and facial appearance) to whom the subject is lying can influence physiological and behavioral changes, the experiment included four different interviewers. The interviewer was represented by a photograph of a face that met the required parameters in terms of gender and facial appearance (i.e., interviewer likability/antipathy) to follow standardized procedures. The subject provided all information to the simulated interviewer. During follow-up analyzes, facial temperature (main ROIs: forehead, cheeks, the tip of the nose, chin, and corners of the eyes), heart rate, emotional expression, intensity and fixation of eye movements and pupil dilation were observed. The results showed that the variables studied varied with respect to the production of prepared truths and lies versus the production of spontaneous truths and lies, as well as the variability of the simulated interviewer. The results also supported the assumption of variability in physiological and behavioural values during the subject's resting state, the so-called baseline, and the production of prepared and spontaneous truths and lies. A series of psychophysiological experiments provided evidence of variability in the areas of interest in the production of truths and lies to different interviewers. The combination of technologies used also led to a comprehensive assessment of the physiological and behavioral changes associated with false and true statements. The study presented here opens the space for further research in the field of lie detection with non-contact technologies.

Keywords: emotional expression decoding, eye-tracking, functional infrared thermal imaging, non-contact deception detection, psychophysiological experiment

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Authors: Massimiliano Condotta, Paolo Ruggeri, Chiara Scanagatta, Giovanni Borga

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Architects and urban planners, when designing and renewing cities, have to face a complex set of problems, including the issues of noise and air pollution which are considered as hot topics (i.e., the Clean Air Act of London and the Soundscape definition). It is usually taken for granted that these problems go by together because the noise pollution present in cities is often linked to traffic and industries, and these produce air pollutants as well. Traffic congestion can create both noise pollution and air pollution, because NO₂ is mostly created from the oxidation of NO, and these two are notoriously produced by processes of combustion at high temperatures (i.e., car engines or thermal power stations). We can see the same process for industrial plants as well. What have to be investigated – and is the topic of this paper – is whether or not there really is a correlation between noise pollution and air pollution (taking into account NO₂) in urban areas. To evaluate if there is a correlation, some low-cost methodologies will be used. For noise measurements, the OpeNoise App will be installed on an Android phone. The smartphone will be positioned inside a waterproof box, to stay outdoor, with an external battery to allow it to collect data continuously. The box will have a small hole to install an external microphone, connected to the smartphone, which will be calibrated to collect the most accurate data. For air, pollution measurements will be used the AirMonitor device, an Arduino board to which the sensors, and all the other components, are plugged. After assembling the sensors, they will be coupled (one noise and one air sensor) and placed in different critical locations in the area of Mestre (Venice) to map the existing situation. The sensors will collect data for a fixed period of time to have an input for both week and weekend days, in this way it will be possible to see the changes of the situation during the week. The novelty is that data will be compared to check if there is a correlation between the two pollutants using graphs that should show the percentage of pollution instead of the values obtained with the sensors. To do so, the data will be converted to fit on a scale that goes up to 100% and will be shown thru a mapping of the measurement using GIS methods. Another relevant aspect is that this comparison can help to choose which are the right mitigation solutions to be applied in the area of the analysis because it will make it possible to solve both the noise and the air pollution problem making only one intervention. The mitigation solutions must consider not only the health aspect but also how to create a more livable space for citizens. The paper will describe in detail the methodology and the technical solution adopted for the realization of the sensors, the data collection, noise and pollution mapping and analysis.

Keywords: air quality, data analysis, data collection, NO₂, noise mapping, noise pollution, particulate matter

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Authors: Ranjith Maniyeri, Ahamed C. Saleel

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Two-dimensional fluid flow over a stationary circular cylinder is one of the bench mark problem in the field of fluid-structure interaction in computational fluid dynamics (CFD). Motivated by this, in the present work, a two-dimensional computational model is developed using an improved version of immersed boundary method which combines the feedback forcing scheme of the virtual boundary method with Peskin’s regularized delta function approach. Lagrangian coordinates are used to represent the cylinder and Eulerian coordinates are used to describe the fluid flow. A two-dimensional Dirac delta function is used to transfer the quantities between the sold to fluid domain. Further, continuity and momentum equations governing the fluid flow are solved using fractional step based finite volume method on a staggered Cartesian grid system. The developed code is validated by comparing the values of drag coefficient obtained for different Reynolds numbers with that of other researcher’s results. Also, through numerical simulations for different Reynolds numbers flow behavior is well captured. The stability analysis of the improved version of immersed boundary method is tested for different values of feedback forcing coefficients.

Keywords: Feedback Forcing Scheme, Finite Volume Method, Immersed Boundary Method, Navier-Stokes Equations

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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Authors: Santanu Pakhira, Chandan Mazumdar, R. Ranganathan, Maxim Avdeev

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Magnetically frustrated systems are of great interest and one of the most adorable topics for the researcher of condensed matter physics, due to their various interesting properties, viz. ground state degeneracy, finite entropy at zero temperature, lowering of ordering temperature, etc. Ternary intermetallics with the composition RE₂TX₃ (RE = rare-earth element, T= d electron transition metal and X= p electron element) crystallize in hexagonal AlB₂ type crystal structure (space group P6/mmm). In a hexagonal crystal structure with the antiferromagnetic interaction between the moments, the center moment is geometrically frustrated. Magnetic frustration along with disorder arrangements of non-magnetic ions are the building blocks for metastable spin-glass ground state formation for most of the compounds of this stoichiometry. The newly synthesized compound Er₂NiSi₃ compound forms in single phase in AlB₂ type structure with space group P6/mmm. The compound orders antiferromagnetically below 5.4 K and spin freezing of the frustrated magnetic moments occurs below 3 K for the compound. The compound shows magnetic relaxation behavior and magnetic memory effect below its freezing temperature. Neutron diffraction patterns for temperatures below the spin freezing temperature have been analyzed using FULLPROF software package. Diffuse magnetic scattering at low temperatures yields spin glass state formation for the compound.

Keywords: antiferromagnetism, magnetic frustration, spin-glass, neutron diffraction

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Authors: Zahra Afshordi

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Instagram, as an everyday life social network, hosts from the ultrasound image of an unborn fetus to the pictures of newly placed gravestones and funerals. It is a platform that allows its users to create a second identity independently from and at the same time in relation to the real space identity. The motives behind this identification are what this article is about. This article studies the motivations of Instagram users mourning for celebrities with a focus on the death of MohammadReza Shajarian. The Shajarian’s death had a wide reflection on Instagram Persian-speaking users. The purpose of this qualitative survey is to comprehend and study the user’s motivations in posting mourning and memorializing content. The methodology of the essay is a hybrid methodology consisting of content analysis and open-ended interviews. The results highlight that users' motives are more than just simple sympathy and include political protest, gaining cultural capital, reaching social status, and escaping from solitude.

Keywords: case study, celebrity, identity, Instagram, mourning, qualitative survey

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Authors: Akbar Nawaz Khan, Abdul Ghaffar, Muhammad Naeem Riaz

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The study was conducted to investigate the phenotypic features, morphometry and production potentialities of indigenous naked neck chicken (NN) of Pakistan under intensive management condition. A total of 35 NN chicks were randomly selected, and the experiment was performed at Poultry and wildlife research section NARC Islamabad for a period of 22 weeks. The predominant plumage color was black and golden while skin color was observed white. The average shank length, leg length, thigh length, keel length, chest breadth, head width, wing space, wing length, body length, body girth, body height and pubic bone width in adult males and females were 69.19 ± 3.34mm, 117.93 ± 4.42mm, 117.93 ± 4.42mm, 90.87 ± 6.53mm, 95.03 ± 4.56mm, 49.77 ± 2.53mm, 30.63 ± 1.50cm, 27.24 ± 2.71cm, 18.88 ± 0.65cm, 17.77 ± 1.01cm, 25.96 ± 0.56cm, 47.81 ± 1.41cm and 35.69 ± 4.09mm respectively. The average age and live body weight of NN chicken at sexual maturity were recorded as 165.85 days and 1269.38 g. While hen-day egg production of NN was recorded as 45%. The present study was aimed to investigate the existence of polymorphism at IGF-I gene in indigenous naked neck chicken through PCR based Restriction Fragment Length Polymorphism. Based on restriction analysis using Hinf I restriction enzyme, three genotypes were detected designated as AA, AC, and CC. Restriction analysis of PCR amplified product showed the presence of DNA fragments of 622, 378, 244 and 191, (genotypes). The PCR-RFLP analysis is easy, cost effective method which permits the easy characterization of IGF-I gene. This showed the investigated IGF-I genes can serve as good molecular markers for marker assisted selection (MAS) concerning growth related traits in chicken.

Keywords: Desi chicken, naked neck, morphology, morphometry, production potential, egg traits, egg geometry, IGF-I, growth, PCR- RFLP, chicken

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Authors: M. Abouelatta, A. Shaker, M. El-Banna, G. T. Sayah, C. Gontrand, A. Zekry

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In this paper, a methodology for physically modeling the intrinsic MOS part and the drift region of the n-channel Laterally Double-diffused MOSFET (LDMOS) is presented. The basic physical effects like velocity saturation, mobility reduction, and nonuniform impurity concentration in the channel are taken into consideration. The analytical model is implemented using MATLAB. A comparison of the simulations from technology computer aided design (TCAD) and that from the proposed analytical model, at room temperature, shows a satisfactory accuracy which is less than 5% for the whole voltage domain.

Keywords: LDMOS, MATLAB, RESURF, modeling, TCAD

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Authors: Noor Farizah Ibrahim, Christopher Durugbo

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This study aims to investigate how the Twittersphere reacted during the recent historical event of robotic landing on a comet. The news is about Philae, a robotic lander from European Space Agency (ESA), which successfully made the first-ever rendezvous and touchdown of its kind on a nucleus comet on November 12, 2014. In order to understand how Twitter is practically used in spreading messages on historical events, we conducted an analysis of one-week tweet feeds that contain the #CometLanding hashtag. We studied the trends of tweets, the diffusion of the information and the characteristics of the social network created. The results indicated that the use of Twitter as a platform enables online communities to engage and spread the historical event through social media network (e.g. tweets, retweets, mentions and replies). In addition, it was found that comprehensible and understandable hashtags could influence users to follow the same tweet stream compared to other laborious hashtags which were difficult to understand by users in online communities.

Keywords: diffusion of information, hashtag, social media, Twitter

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Authors: Lauren E. Church

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Background: Extravehicular activities (EVAs) are a critical aspect of missions aboard the International Space Station (ISS). It has long been noted that the spaceflight environment and the physical demands of EVA cause physiological and metabolic changes in humans; this review aims to combine these findings with nutritional studies in analogues of the spaceflight and EVA environments to make nutritional recommendations for astronauts scheduled for and immediately returning from EVAs. Results: Energy demands increase during orbital spaceflight and see further increases during EVA. Another critical element of EVA nutrition is adequate hydration. Orbital EVA appears to provide adequate hydration under current protocol, but during lunar surface EVA (LEVA) and in a 10km lunar walk-back test astronauts have stated that up to 20% more water was needed. Previous attempts for in-suit edible sustenance have not been adequately taken up by astronauts to be economically viable. In elite endurance athletes, a mixture of glucose and fructose is used in gels, improving performance. Discussion: A combination of non-caffeinated energy drink and simple water should be available for astronauts during EVA, allowing more autonomy. There should also be provision of gels or a similar product containing appropriate sodium levels to maintain hydration, but not so much as to hyperhydrate through renal water reabsorption. It is also suggested that short breaks be built into the schedule of EVAs for these gels to be consumed, as it is speculated that reason for low uptake of in-suit sustenance is the lack of time available in which to consume it.

Keywords: astronaut, nutrition, space, sport

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Authors: Isaac Dery

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Masculinity studies have gained much purchase globally in recent decades, especially the sense in which they have produced discursive space for interdisciplinary investigations. In the light of this, there is increasing consensus among commentators that different masculinities co-exist within a particular social space. There is also a growing recognition and awareness of the merits in examining the conceptual underpinnings of masculinity (especially hegemonic masculinity) its variously contested meanings, and values, and how it contributes to violent behaviours by men. The consequences of hegemonic masculinity and its violent and traumatic impacts on men and women have been evident. The emerging call to imagine more egalitarian and complex masculinities among men has been at the centre of various discussions on the fight against violence. Some theorists argue that this violence emanates from men’s drive to live up to impossible ideals of “masculinity.” Seeking to make the connections between masculinity and gender-based violence, this paper discusses the imperative and possibilities of engaging men/boys as key actors in the campaign against violence. It is worth re-examining the ways in which men’s embodiment and performance of dangerous masculinities contribute towards violence. This paper therefore argues that empowering men to understand the implications of certain behaviours is the key in an attempt to arrest violence and its traumatic cost. This paper is situated within the thesis that there is a relationship between men’s embodiment and performance of dominant forms of masculinities, on the one hand, and violence against women and other men, on the other. Based on research conducted in northern Ghana on domestic violence, it is the argument of this paper that in order to contain violence against women, conditions of gender construction need to be problematized in a manner that will transform fundamental understandings of gender relations in society.

Keywords: violence against women, masculinities, Ghana, gender

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Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine

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Authors: Paula-Catalina Meirosu

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The economic migration (intra-EU) is a topic of debate in the public space in both countries of origin and countries of destination. Since the 1990s, after the collapse of communist regimes and then the accession of some former communist countries to the EU, the migratory flows of migrants (including Romanian migrants) to EU countries has been increased constantly. Italy is one of the main countries of destination among Romanians since at the moment Italy hosts more than one million Romanian migrants. Based on an interdisciplinary analytical framework focused on the theories in the field of transnationalism, media and migration studies and critical media analysis, this paper investigates the media construction of intra-EU economic migration in the Italian press from two main perspectives. The first point of view is the media representation of Romanian migrants in the Italian press in a specific context: the EU elections in 2014. The second one explores the way in which Romanian journalists use the media in the destinations countries (such as Italy) as a source to address the issue of migration. In this context, the paper focuses on online articles related to the Romanian migrants’ representation in the media before and during the EU elections in two newspapers (La Repubblica from Italy and Adevarul from Romania), published during January-May 2014. The methodology is based on a social-constructivist approach, predominantly discursive and includes elements of critical discourse analysis (CDA) to identify the patterns of Romanian migrants in the Italian press as well as strategies for building categories, identities, and roles of migrants. The aim of such an approach is to find out the dynamic of the media discourse on migration from a destination country in the light of a European electoral context (EU elections) and based on the results, to propose scenarios for the elections to be held this year.

Keywords: migration, media discourse, Romanian migrants, transnationalism

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Authors: Olawale J. Olaluyi, Ayodele S. Oluwole, O. Akinsanmi, Johnson O. Adeogo

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Communication using visible light VLC is considered a cutting-edge technology used for data transmission and illumination since it uses less energy than radio frequency (RF) technology and has a large bandwidth, extended lifespan, and high security. The room's irregular distribution of small base stations, or LED array distribution, is the cause of the obscured area, minimum signal-to-noise ratio (SNR), and received power. In order to maximize the received power distribution and SNR at the center of the room for an indoor VLC system, the researchers offer an innovative model for the placement of eight LED array distributions in this work. We have investigated the arrangement of the LED array distribution with regard to receiving power to fill the open space in the center of the room. The suggested LED array distribution saved 36.2% of the transmitted power, according to the simulation findings. Aside from that, the entire room was equally covered. This leads to an increase in both received power and SNR.

Keywords: visible light communication (VLC), light emitted diodes (LED), optical power distribution, signal-to-noise ratio (SNR).

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Authors: Gyula I. Tóth, Shaho Abdalla

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Even though numerical simulations indeed have a significant precursory/supportive role in exploring the disordered phase displaying no long-range order in pattern formation models, studying the stability properties of this phase and determining the order of the ordered-disordered phase transition in these models necessitate an analytical description of the disordered phase. First, we will present the results of a comprehensive statistical analysis of a large number (1,000-10,000) of numerical simulations in the Swift-Hohenberg model, where the bulk disordered (or amorphous) phase is stable. We will show that the average free energy density (over configurations) converges, while the variance of the energy density vanishes with increasing system size in numerical simulations, which suggest that the disordered phase is a thermodynamic phase (i.e., its properties are independent of the configuration in the macroscopic limit). Furthermore, the structural analysis of this phase in the Fourier space suggests that the phase can be modeled by a colored isotropic Gaussian noise, where any instant of the noise describes a possible configuration. Based on these results, we developed the general mathematical framework of finding a pool of solutions to partial differential equations in the sense of continuous probability measure, which we will present briefly. Applying the general idea to the Swift-Hohenberg model we show, that the amorphous phase can be found, and its properties can be determined analytically. As the general mathematical framework is not restricted to continuum theories, we hope that the proposed methodology will open a new chapter in studying disordered phases.

Keywords: fundamental theory, mathematical physics, continuum models, analytical description

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Authors: Hye-Young Shin, Chan Kee Park

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Background: To compare the thinning patterns of the ganglion cell-inner plexiform layer (GCIPL) and peripapillary retinal nerve fiber layer (pRNFL) as measured using Cirrus high-definition optical coherence tomography (HD-OCT) in patients with visual field (VF) defects that respect the vertical meridian. Methods: Twenty eyes of eleven patients with VF defects that respect the vertical meridian were enrolled retrospectively. The thicknesses of the macular GCIPL and pRNFL were measured using Cirrus HD-OCT. The 5% and 1% thinning area index (TAI) was calculated as the proportion of abnormally thin sectors at the 5% and 1% probability level within the area corresponding to the affected VF. The 5% and 1% TAI were compared between the GCIPL and pRNFL measurements. Results: The color-coded GCIPL deviation map showed a characteristic vertical thinning pattern of the GCIPL, which is also seen in the VF of patients with brain lesions. The 5% and 1% TAI were significantly higher in the GCIPL measurements than in the pRNFL measurements (all P < 0.01). Conclusions: Macular GCIPL analysis clearly visualized a characteristic topographic pattern of retinal ganglion cell (RGC) loss in patients with VF defects that respect the vertical meridian, unlike pRNFL measurements. Macular GCIPL measurements provide more valuable information than pRNFL measurements for detecting the loss of RGCs in patients with retrograde degeneration of the optic nerve fibers.

Keywords: brain lesion, macular ganglion cell, inner plexiform layer, spectral-domain optical coherence tomography

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Authors: Misty Attwood, Helgi Schioth

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Transmembrane proteins are important components in many essential cell processes such as signal transduction, cell-cell signalling, transport of solutes, structural adhesion activities, and protein trafficking. Due to their involvement in diverse critical activities, transmembrane proteins are implicated in different disease pathways and hence are the focus of intense interest in understanding functional activities, their pathogenesis in disease, and their potential as pharmaceutical targets. Further, as the structure and function of proteins are correlated, investigating a group of proteins with the same tertiary structure, i.e., the same number of transmembrane regions, may give understanding about their functional roles and potential as therapeutic targets. In this in silico bioinformatics analysis, we identify and comprehensively characterize the previously unstudied group of proteins with five transmembrane-spanning regions (5TM). We classify nearly 60 5TM proteins in which 31 are members of ten families that contain two or more family members and all members are predicted to contain the 5TM architecture. Furthermore, nine singlet proteins that contain the 5TM architecture without paralogues detected in humans were also identifying, indicating the evolution of single unique proteins with the 5TM structure. Interestingly, more than half of these proteins function in localization activities through movement or tethering of cell components and more than one-third are involved in transport activities, particularly in the mitochondria. Surprisingly, no receptor activity was identified within this family in sharp contrast with other TM families. Three major 5TM families were identified and include the Tweety family, which are pore-forming subunits of the swelling-dependent volume regulated anion channel in astrocytes; the sidoreflexin family that acts as mitochondrial amino acid transporters; and the Yip1 domain family engaged in vesicle budding and intra-Golgi transport. About 30% of the proteins have enhanced expression in the brain, liver, or testis. Importantly, 60% of these proteins are identified as cancer prognostic markers, where they are associated with clinical outcomes of various tumour types, indicating further investigation into the function and expression of these proteins is important. This study provides the first comprehensive analysis of proteins with 5TM regions and provides details of the unique characteristics and application in pharmaceutical development.

Keywords: 5TM, cancer prognostic marker, drug targets, transmembrane protein

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Authors: Omer Burak Iskender, Keck Voon Ling, Vincent Dubanchet, Luca Simonini

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This paper presents Guidance and Control (G&C) strategy to approach and synchronize with potentially rotating targets. The proposed strategy generates and tracks a safe trajectory for space servicing missions, including tasks like approaching, inspecting, and capturing. The main objective of this paper is to validate the G&C laws using a Hardware-In-the-Loop (HIL) setup with realistic rendezvous and docking equipment. Throughout this work, the assumption of full relative state feedback is relaxed by onboard sensors that bring realistic errors and delays and, while the proposed closed loop approach demonstrates the robustness to the above mentioned challenge. Moreover, G&C blocks are unified via the Model Predictive Control (MPC) paradigm, and the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description. In this work, G&C is formulated as a convex optimization problem where constraints such as thruster limits and the output constraints are explicitly handled. Furthermore, the Monte-Carlo method is used to evaluate the robustness of the proposed method to the initial condition errors, the uncertainty of the target's motion and attitude, and actuator errors. A capture scenario is tested with the robotic test bench that has onboard sensors which estimate the position and orientation of a drifting satellite through camera imagery. Finally, the approach is compared with currently used robust H-infinity controllers and guidance profile provided by the industrial partner. The HIL experiments demonstrate that the proposed strategy is a potential candidate for future space servicing missions because 1) the algorithm is real-time implementable as convex programming offers deterministic convergence properties and guarantee finite time solution, 2) critical physical and output constraints are respected, 3) robustness to sensor errors and uncertainties in the system is proven, 4) couples translational motion with rotational motion.

Keywords: dual quaternion, model predictive control, real-time experimental test, rendezvous and docking, spacecraft autonomy, space servicing

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Authors: Monika Zalewska

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Hans Kelsen was a versatile legal thinker whose achievements in the fields of legal theory, international law, and the theory of democracy are remarkable. All of the fields tackled by Kelsen are regarded as part of his “pure theory of law.” While the link between international law and Kelsen’s pure theory of law is apparent, the same cannot be said about the link between the theory of democracy and his pure theory of law. On the contrary, the general thinking concerning Kelsen’s thought is that it can be used to legitimize authoritarian regimes. The aim of this presentation is to address this concern by identifying the common ground between Kelsen’s pure theory of law and his theory of democracy and to show that they are compatible in a way that his pure theory of law and authoritarianism cannot be. The conceptual analysis of the purity of Kelsen’s theory and his goal of creating ideology-free legal science hints at how Kelsen’s pure theory of law and the theory of democracy are brought together. The presentation will first demonstrate that these two conceptions have common underlying values and meta-ethical convictions. Both are founded on relativism and a rational worldview, and the aim of both is peaceful co-existence. Second, it will be demonstrated that the separation of law and morality provides the maximum space for deliberation within democratic processes. The conclusion of this analysis is that striking similarities exist between Kelsen’s legal theory and his theory of democracy. These similarities are grounded in the Enlightenment tradition and its values, including rationality, a scientific worldview, tolerance, and equality. This observation supports the claim that, for Kelsen, legal positivism and the theory of democracy are not two separate theories but rather stem from the same set of values and from Kelsen’s relativistic worldview. Furthermore, three main issues determine Kelsen’s orientation toward a positivistic and democratic outlook. The first, which is associated with personality type, is the distinction between absolutism and relativism. The second, which is associated with the values that Kelsen favors in the social order, is peace. The third is legality, which creates the necessary condition for democracy to thrive and reveals that democracy is capable of fulfilling Kelsen’s ideal of law at its fullest. The first two categories exist in the background of Kelsen’s pure theory of law, while the latter is an inherent part of Kelsen’s concept of law. The analysis of the text concerning natural law doctrine and democracy indicates that behind the technical language of Kelsen’s pure theory of law is a strong concern with the trends that appeared after World War I. Despite his rigorous scientific mind, Kelsen was deeply humanistic. He tried to create a powerful intellectual weapon to provide strong arguments for peaceful coexistence and a rational outlook in Europe. The analysis provided by this presentation facilitates a broad theoretical, philosophical, and political understanding of Kelsen’s perspectives and, consequently, urges a strong endorsement of Kelsen’s approach to constitutional democracy.

Keywords: hans kelsen, democracy, legal positivism, pure theory of law

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Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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Authors: M. G. N. A. S. Fernando

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This study uses a researchable framework to improve the quality of ICT education and the Teaching Learning Assessment/ Evaluation (TLA/TLE) process. It utilizes existing resources while improving the methodologies along with pedagogical techniques and e-Learning approaches used in the secondary schools of Sri Lanka. The study was carried out in two phases. Phase I focused on investigating the factors which affect the quality of ICT education. Based on the key factors of phase I, the Phase II focused on the design of an Experimental Application Model with 6 activity levels. Each Level in the Activity Model covers one or more levels in the Revised Bloom’s Taxonomy. Towards further enhancement of activity levels, other pedagogical techniques (activity based learning, e-learning techniques, problem solving activities and peer discussions etc.) were incorporated to each level in the activity model as appropriate. The application model was validated by a panel of teachers including a domain expert and was tested in the school environment too. The validity of performance was proved using 6 hypotheses testing and other methodologies. The analysis shows that student performance with problem solving activities increased by 19.5% due to the different treatment levels used. Compared to existing process it was also proved that the embedded techniques (mixture of traditional and modern pedagogical methods and their applications) are more effective with skills development of teachers and students.

Keywords: activity models, Bloom’s taxonomy, ICT education, pedagogies

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Authors: Aabha Chaubey, Bani Bhattacharya

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Evaluation of the quality of teaching in engineering education in India needs to be conducted on a continuous basis to achieve the best teaching quality in technical education. Quality teaching is an influential factor in technical education which impacts largely on learning outcomes of the students. Present study is not exclusively theory-driven, but it draws on various specific concepts and constructs in the domain of technical education. These include teaching and learning in higher education, teacher effectiveness, and teacher evaluation and performance management in higher education. Student Evaluation of Education Quality (SEEQ) was proposed as one of the evaluation instruments of the quality teaching in engineering education. SEEQ is one of the popular and standard instrument widely utilized all over the world and bears the validity and reliability in educational world. The present study was designed to evaluate the teaching quality through SEEQ in the context of technical education in India, including its validity and reliability based on the collected data. The multiple dimensionality of SEEQ that is present in every teaching and learning process made it quite suitable to collect the feedback of students regarding the quality of instructions and instructor. The SEEQ comprises of 9 original constructs i.e.; learning value, teacher enthusiasm, organization, group interaction, and individual rapport, breadth of coverage, assessment, assignments and overall rating of particular course and instructor with total of 33 items. In the present study, a total of 350 samples comprising first year undergraduate students from Indian Institute of Technology, Kharagpur (IIT, Kharagpur, India) were included for the evaluation of the importance of SEEQ. They belonged to four different courses of different streams of engineering studies. The above studies depicted the validity and reliability of SEEQ was based upon the collected data. This further needs Confirmatory Factor Analysis (CFA) and Analysis of Moment structure (AMOS) for various scaled instrument like SEEQ Cronbach’s alpha which are associated with SPSS for the examination of the internal consistency. The evaluation of the effectiveness of SEEQ in CFA is implemented on the basis of fit indices such as CMIN/df, CFI, GFI, AGFI and RMSEA readings. The major findings of this study showed the fitness indices such as ChiSq = 993.664,df = 390,ChiSq/df = 2.548,GFI = 0.782,AGFI = 0.736,CFI = 0.848,RMSEA = 0.062,TLI = 0.945,RMR = 0.029,PCLOSE = 0.006. The final analysis of the fit indices presented positive construct validity and stability, on the other hand a higher reliability was also depicted which indicated towards internal consistency. Thus, the study suggests the effectivity of SEEQ as the indicator of the quality evaluation instrument in teaching-learning process in engineering education in India. Therefore, it is expected that with the continuation of this research in engineering education there remains a possibility towards the betterment of the quality of the technical education in India. It is also expected that this study will provide an empirical and theoretical logic towards locating a construct or factor related to teaching, which has the greatest impact on teaching and learning process in a particular course or stream in engineering education.

Keywords: confirmatory factor analysis, engineering education, SEEQ, teaching and learning process

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Authors: Fortaki Tarek, S. Bedra

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In this paper, the effects of both uniaxial anisotropy in the substrate and high Tc superconducting patch on the resonant frequency, half-power bandwidth, and radiation patterns are investigated using an electric field integral equation and the spectral domain Green’s function. The analysis has been based on a full electromagnetic wave model with London’s equations and the Gorter-Casimir two-fluid model has been improved to investigate the resonant and radiation characteristics of high Tc superconducting rectangular microstrip patch in the case where the patch is printed on electric-magnetic uniaxially anisotropic substrate materials. The stationary phase technique has been used for computing the radiation electric field. The obtained results demonstrate a considerable improvement in the half-power bandwidth, of the rectangular microstrip patch, by using a superconductor patch instead of a perfect conductor one. Further results show that high Tc superconducting rectangular microstrip patch on the uniaxial substrate with properly selected electric and magnetic anisotropy ratios is more advantageous than the one on the isotropic substrate by exhibiting wider bandwidth and radiation characteristic. This behavior agrees with that discovered experimentally for superconducting patches on isotropic substrates. The calculated results have been compared with measured one available in the literature and excellent agreement has been found.

Keywords: high Tc superconducting microstrip patch, electric-magnetic anisotropic substrate, Galerkin method, surface complex impedance with boundary conditions, radiation patterns

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Authors: Mohammad Alhajeri

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This paper reports a computational fluid dynamics (CFD) investigation of cylindrical filter. Silicon carbide cylindrical filter elements have proven to be an effective mean of removing particulates to levels exceeding the new source performance standard. The CFD code is used here to understand the deposition process and the factors that affect the particles distribution over the filter element surface. Different approach cross flow velocity to filter face velocity ratios and different face velocities (ranging from 2 to 5 cm/s) are used in this study. Particles in the diameter range 1 to 100 microns are tracked through the domain. The radius of convergence (or the critical trajectory) is compared and plotted as a function of many parameters.

Keywords: filtration, CFD, CCF, hot gas filtration

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Authors: Jiraporn Rojtinnakorn

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ICAM-2 (intercellular adhesion molecule 2) or CD102 (Cluster of Differentiation 102) is type I trans-membrane glycoproteins, composing 2-9 immunoglobulin-like C2-type domains. ICAM-2 plays the particular role in immune response and cell surveillance. It is concerned in innate and specific immunity, cell survival signal, apoptosis, and anticancer. EST clone of ICAM-2, from P. gigas blood cell EST libraries, showed high identity to human ICAM-2 (92%) with conserve region of ICAM N-terminal domain and part of Ig superfamily. Gene and protein of ICAM-2 has been founded in mammals. This is the first report of ICAM-2 in fish.

Keywords: ICAM-2, CD102, Pangasianodon gigas, antitumor

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Authors: Hasan Fatih Ertuğrul, Beytullah Okur, Huseyin Üvet, Kadir Erkan

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The objective of this paper is to analyze a 4-pole hybrid magnetic levitation system by using 3D finite element and analytical methods. The magnetostatic analysis of the system is carried out by using ANSYS MAXWELL-3D package. An analytical model is derived by magnetic equivalent circuit (MEC) method. The purpose of magnetostatic analysis is to determine the characteristics of attractive force and rotational torques by the change of air gap clearances, inclination angles and current excitations. The comparison between 3D finite element analysis and analytical results are presented at the rest of the paper.

Keywords: yoke hybrid electromagnet, 3D finite element analysis, magnetic levitation system, magnetostatic analysis

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Authors: Deepak Singh, Rail Kuliev

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This research article explores the significance of advanced data visualization techniques in enhancing decision-making processes within the oil and gas exploration and production domain. With the oil and gas industry facing numerous challenges, effective interpretation and analysis of vast and diverse datasets are crucial for optimizing exploration strategies, production operations, and risk assessment. The article highlights the importance of data visualization in managing big data, aiding the decision-making process, and facilitating communication with stakeholders. Various advanced data visualization techniques, including 3D visualization, augmented reality (AR), virtual reality (VR), interactive dashboards, and geospatial visualization, are discussed in detail, showcasing their applications and benefits in the oil and gas sector. The article presents case studies demonstrating the successful use of these techniques in optimizing well placement, real-time operations monitoring, and virtual reality training. Additionally, the article addresses the challenges of data integration and scalability, emphasizing the need for future developments in AI-driven visualization. In conclusion, this research emphasizes the immense potential of advanced data visualization in revolutionizing decision-making processes, fostering data-driven strategies, and promoting sustainable growth and improved operational efficiency within the oil and gas exploration and production industry.

Keywords: augmented reality (AR), virtual reality (VR), interactive dashboards, real-time operations monitoring

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Authors: Ju-Young Hwang, Hyo-Gyoung Kwak

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This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical nonlinearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC, high temperature, after-cooling analysis, nonlinear analysis

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Authors: Sergey N. Sayapin, Anatoly P. Karpenko, Suan H. Dang

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Comparative analysis of robotic vehicles for pipe inspection is presented in this paper. The promising concept of self-propelled intelligent robotic vehicle (SPIRV) based on octahedral dodekapod for inspection and operation in active branched pipelines with variable cross-sections is reasoned. SPIRV is able to move in pipeline, regardless of its spatial orientation. SPIRV can also be used to move along the outside of the pipelines as well as in space between surfaces of annular tubes. Every one of faces of the octahedral dodekapod can clamp/unclamp a thing with a closed loop surface of various forms as well as put pressure on environmental surface of contact. These properties open new possibilities for its applications in SPIRV. We examine design principles of octahedral dodekapod as future intelligent building blocks for various robotic vehicles that can self-move and self-reconfigure.

Keywords: Modular robot, octahedral dodekapod, pipe inspection robot, spatial parallel structure

Procedia PDF Downloads 492