Search results for: finite element (FE) model

Authors: Kazuyoshi Mori

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In this paper, we consider the number of parameters for the parametrization of stabilizing controllers for RHinf systems with size 2 × 2. Fortunately, any plant of this model can admit doubly coprime factorization. Thus we can use the Youla parameterization to parametrize the stabilizing contollers . However, Youla parameterization does not give itself the minimal number of parameters. This paper shows that the minimal number of parameters is four. As a result, we show that the Youla parametrization naturally gives the parameterization of stabilizing controllers with minimal numbers.

Keywords: RHinfo, parameterization, number of parameters, multi-input, multi-output systems

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Authors: Zhongzhi Hu, Jie Shen, Jiqiang Wang

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A high precision aeroengine model is needed when developing the engine control system. Compared with other main components, the axial compressor is the most challenging component to simulate. In this paper, a compressor map optimizing tool based on the introduction of a modifiable β function is developed for FWorks (FADEC Works). Three parameters (d density, f fitting coefficient, k₀ slope of the line β=0) are introduced to the β function to make it modifiable. The comparison of the traditional β function and the modifiable β function is carried out for a certain type of compressor. The interpolation errors show that both methods meet the modeling requirements, while the modifiable β function can predict compressor performance more accurately for some areas of the compressor map where the users are interested in.

Keywords: beta function, compressor map, interpolation error, map optimization tool

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Authors: Hussain Bunyan, Wesam Ali

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In this paper we will study the performance of a Silicon Photovoltaic (PV) system with different tilt angle arrangement in Kuwait (latitude 30˚ N). In this study the PV system is installed facing south, collecting maximum solar radiation at noon, and their angles are from 00 to 900 respectively, during full year at the Solstice and Equinox periods and aiming for a higher angle than 300 with competitive output power. The results show that the performance and the output power of the PV system with 50˚ tilt angle, is equivalent to the latitude tilt angle (30˚) during a full year.

Keywords: photovoltaic model, tilt angle, solar collector, PV system performance, State of Kuwait

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Authors: Ali Asghar Memon

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A cautious and astute selection of switching devices used in power electronic converters of a switched reluctance (SR) motor is required. It is a matter of choice of best switching devices with respect to their switching ability rather than fulfilling the number of switches. This paper highlights the computational determination of switching losses comprising of switch-on, switch-off and conduction losses respectively by using experimental data in simulation model of a SR machine. The finding of this research is helpful for proper selection of electronic switches and suitable converter topology for switched reluctance motor.

Keywords: converter, operating modes, switched reluctance motor, switching losses

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Authors: Hussain Bunyan, Wesam Ali

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In this paper we will study the performance of a Silicon Photovoltaic (PV) system with different tilt angle arrangement in Kuwait (latitude 30˚ N). In the study the PV system is installed facing South, collecting maximum solar radiation at noon, and their angles are from 00 to 900 respectively, during full year at the Solstice and Equinox periods, aiming for a higher angle than 300 with competitive output power. The results show that the performance and the output power of the PV system with 50˚ tilt angle, is equivalent to the latitude tilt angle (30˚) during a full year.

Keywords: photovoltaic model, tilt angle, solar collector, PV system performance, State of Kuwait

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Authors: Nicholas Fletcher, Zachary Houston, Yongmei Zhao, Christopher Howard, Kristofer Thurecht

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One promising approach to enhance nanomedicine therapeutic efficacy is to include a targeting agent, such as an antibody, to increase accumulation at the tumor site. However, the application of such targeted nanomedicines remains limited, in part due to difficulties involved with biomolecule conjugation to synthetic nanomaterials. One approach recently developed to overcome this has been to engineer bispecific antibodies (BsAbs) with dual specificity, whereby one portion binds to methoxy polyethyleneglycol (mPEG) epitopes present on synthetic nanomedicines, while the other binds to molecular disease markers of interest. In this way, noncovalent complexes of nanomedicine core, comprising a hyperbranched polymer (HBP) of primarily mPEG, decorated with targeting ligands are able to be produced by simple mixing. Further work in this area has now demonstrated such complexes targeting the breast cancer marker epidermal growth factor receptor (EGFR) to show enhanced binding to tumor cells both in vitro and in vivo. Indeed the enhanced accumulation at the tumor site resulted in improved therapeutic outcomes compared to untargeted nanomedicines and free chemotherapeutics. The current work on these BsAb-HBP conjugates focuses on further probing antibody-nanomaterial interactions and demonstrating broad applicability to a range of cancer types. Herein are reported BsAb-HBP materials targeted towards prostate-specific membrane antigen (PSMA) and study of their behavior in vivo using ⁸⁹Zr positron emission tomography (PET) in a dual-tumor prostate cancer xenograft model. In this model mice bearing both PSMA+ and PSMA- tumors allow for PET imaging to discriminate between nonspecific and targeted uptake in tumors, and better quantify the increased accumulation following BsAb conjugation. Also examined is the potential for formation of these targeted complexes in situ following injection of individual components? The aim of this approach being to avoid undesirable clearance of proteinaceous complexes upon injection limiting available therapeutic. Ultimately these results demonstrate BsAb functionalized nanomaterials as a powerful and versatile approach for producing targeted nanomedicines for a variety of cancers.

Keywords: bioengineering, cancer, nanomedicine, polymer chemistry

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Authors: Jennifer Knudsen

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This study observes the moderating effects of family structure on College Achievement across cohorts. Over the past half-century, social stigmas surrounding non-traditional families have shifted, as they make up an increasing proportion of American families. Using the General Social Survey, this study employs a varying coefficient model to test if family structure moderates the effects of other background variables on respondents’ educational attainment. Initial analysis suggests that living in alternative family arrangements has an increasingly negative effect on college achievement, whereas living in an intact family with a mother and father has a positive effect on college achievement.

Keywords: education, family, college, family structure

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Authors: Younis Elhaddad, Alfonso Ortega

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Oil production by means of gas lift is a standard technique in oil production industry. To optimize the total amount of oil production in terms of the amount of gas injected is a key question in this domain. Different methods have been tested to propose a general methodology. Many of them apply well-known numerical methods. Some of them have taken into account the power of evolutionary approaches. Our goal is to provide the experts of the domain with a powerful automatic searching engine into which they can introduce their knowledge in a format close to the one used in their domain, and get solutions comprehensible in the same terms, as well. These proposals introduced in the genetic engine the most expressive formal models to represent the solutions to the problem. These algorithms have proven to be as effective as other genetic systems but more flexible and comfortable for the researcher although they usually require huge search spaces to justify their use due to the computational resources involved in the formal models. The first step to evaluate the viability of applying our approaches to this realm is to fully understand the domain and to select an instance of the problem (gas lift optimization) in which applying genetic approaches could seem promising. After analyzing the state of the art of this topic, we have decided to choose a previous work from the literature that faces the problem by means of numerical methods. This contribution includes details enough to be reproduced and complete data to be carefully analyzed. We have designed a classical, simple genetic algorithm just to try to get the same results and to understand the problem in depth. We could easily incorporate the well mathematical model, and the well data used by the authors and easily translate their mathematical model, to be numerically optimized, into a proper fitness function. We have analyzed the 100 curves they use in their experiment, similar results were observed, in addition, our system has automatically inferred an optimum total amount of injected gas for the field compatible with the addition of the optimum gas injected in each well by them. We have identified several constraints that could be interesting to incorporate to the optimization process but that could be difficult to numerically express. It could be interesting to automatically propose other mathematical models to fit both, individual well curves and also the behaviour of the complete field. All these facts and conclusions justify continuing exploring the viability of applying the approaches more sophisticated previously proposed by our research group.

Keywords: evolutionary automatic programming, gas lift, genetic algorithms, oil production

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Authors: Tzu-Ling Hsieh

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When the Taiwan Ministry of Education implemented a new university multiple entrance policy in 2002, most colleges and universities still use testing scores as mainly admission criteria. With forthcoming 12 basic-year education curriculum, the Ministry of Education provides a new college admission policy, which will be implemented in 2021. The new college admission policy will highlight the importance of holistic education by more emphases on the learning process of senior high school, except only on the outcome of academic testing. However, the development of college admission criteria doesn’t have a thoughtful process. Universities and colleges don’t have an idea about how to make suitable multi-admission criteria. Although there are lots of studies in other countries which have implemented multi-college admission criteria for years, these studies still cannot represent Taiwanese students. Also, these studies are limited without the comparison of two different academic fields. Therefore, this study investigated multiple admission criteria and its relationship with college success. This study analyzed the Taiwan Higher Education Database with 12,747 samples from 156 universities and tested a conceptual framework that examines factors by structural equation model (SEM). The conceptual framework of this study was adapted from Pascarella's general causal model and focused on how different admission criteria predict students’ college success. It discussed the relationship between admission criteria and college success, also the relationship how motivation (one of admission standard) influence college success through engagement behaviors of student effort and interactions with agents of socialization. After processing missing value, reliability and validity analysis, the study found three indicators can significantly predict students’ college success which was defined as average grade of last semester. These three indicators are the Chinese language scores at college entrance exam, high school class rank, and quality of student academic engagement. In addition, motivation can significantly predict quality of student academic engagement and interactions with agents of socialization. However, the multi-group SEM analysis showed that there is no difference to predict college success between the students from liberal arts and science. Finally, this study provided some suggestions for universities and colleges to develop multi-admission criteria through the empirical research of Taiwanese higher education students.

Keywords: college admission, admission criteria, structural equation modeling, higher education, education policy

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Authors: Ashish Trivedi, Amol Singh

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In the recent years, the magnitude and frequency of disasters have increased at an alarming rate. Every year, more than 400 natural disasters affect global population. A large-scale disaster leads to destruction or damage to houses, thereby rendering a notable number of residents homeless. Since humanitarian response and recovery process takes considerable time, temporary establishments are arranged in order to provide shelter to affected population. These shelter areas are vital for an effective humanitarian relief; therefore, they must be strategically planned. Choosing the locations of temporary shelter areas for accommodating homeless people is critical to the quality of humanitarian assistance provided after a large-scale emergency. There has been extensive research on the facility location problem both in theory and in application. In order to deliver sufficient relief aid within a relatively short timeframe, humanitarian relief organisations pre-position warehouses at strategic locations. However, such approaches have received limited attention from the perspective of providing shelters to disaster-affected people. In present research work, this aspect of humanitarian logistics is considered. The present work proposes a hybrid decision support model to determine relative preference of potential shelter locations by assessing them based on key subjective criteria. Initially, the factors that are kept in mind while locating potential areas for establishing temporary shelters are identified by reviewing extant literature and through consultation from a panel of disaster management experts. In order to determine relative importance of individual criteria by taking into account subjectivity of judgements, a hybrid approach of fuzzy sets and Analytic Hierarchy Process (AHP) was adopted. Further, Technique for order preference by similarity to ideal solution (TOPSIS) was applied on an illustrative data set to evaluate potential locations for establishing temporary shelter areas for homeless people in a disaster scenario. The contribution of this work is to propose a range of possible shelter locations for a humanitarian relief organization, using a robust multi criteria decision support framework.

Keywords: AHP, disaster preparedness, fuzzy set theory, humanitarian logistics, TOPSIS, temporary shelters

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Authors: Lo Kai Chung

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Fathers in the family of disabled children play a crucial role in fostering child development. Previous studies addressing emotions of father involvement in rearing children with special needs have been rare. With reference to the cultural orientation and masculine idea of Chinese fathers, shame and guilt are probable causal emotions that affect fathers’ psycho-behavioral reactions and, thus, father involvement. Based on the findings of our earlier qualitative studies, the current study aims to develop and validate a multi-item scale of guilt or shame and explore their relations with and fatherhood in families with children with special needs. A model is proposed to understand the roles that shame and guilt play in affecting fathers’ involvement in their family system. The severity and type of the child’s special needs are regarded as independent variables affecting the father’s emotional responses – shame and guilt. It is hypothesized that shame and guilt, under the influence of masculinity, lead to avoidance and compensation, respectively, which subsequently decrease and increase father involvement with children with special needs. A cross-sectional online questionnaire survey of fathers with children with special needs recruited by convenience sampling was conducted. Potential participants were reached by bulk emails, related groups on the Internet and education/social services providers. Totally 537 valid sets of online questionnaires were collected from fathers of children with special needs. EFA on the items pool of shame and guilt was performed, resulting in an x-item single-factor solution and y-item single-factor solution, respectively. Further path model analysis revealed that shame and guilt, under the influence of masculinity, showed differential avoidance and compensation responses and resulted in a decrease and increase in father involvement with special needs children. Demographic and key confounding variables were controlled in the analysis. The shame and guilt scales developed show good psychometric properties. Furthermore, they showed significant differential impacts, under the influence of masculinity, on avoidance and compensation behaviours, consequently resulting in a decrease/increase in father involvement in the expected directions. The findings have important theoretical and practical implications. At the community and policy level, the findings inform the design of strategies for strengthening the role of men in families with special needs children.

Keywords: emotions, father involvement, guilt, shame, special needs

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Authors: Luzie Krings, Sven Liebehentze, Maximilian Gehring, Uwe Rüppel

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The integration of renewable energy into the energy grid is essential for decarbonization, and leveraging electrified vehicles (EVs) as mobile storage units offers a pathway to address grid challenges. The decentralized nature of EVs and the intermittency of renewable energy sources, such as photovoltaic (PV) and wind power, complicate grid stability. Vehicle-to-Grid (V2G) technology presents a promising solution, enabling EVs to support grid stability through services like redispatch, congestion mitigation, and enhanced renewable energy utilization. Freight transport, contributing 38% of transport emissions, holds significant potential as its aggregated energy storage capacity can stabilize the grid and optimize renewable energy integration. This study introduces a risk-averse optimization model for marketing EV flexibilities in Germany’s energy markets, with a strong focus on improving grid stability and maximizing renewable energy potential. Using a linear optimization framework, the model incorporates technical, regulatory, and operational constraints to simulate EV fleets as scalable energy storage solutions. The integration of proprietary PV and wind energy systems is also modeled to evaluate benefits. Benchmarks compare bidirectional charging with unidirectional charging under dynamic tariffs. The methodology employs the Python-based energypilot tool to optimize participation in Day-Ahead, Intraday, and Redispatch markets, accounting for trading conditions and temporal offsets. Results demonstrate that redispatch utilization substantially supports grid stability, while bidirectional charging increased renewable energy integration by 15% and economic benefits by 20%. Longer charging cycles offered greater financial returns compared to fragmented cycles, emphasizing the potential of fleets with extended idle periods for storing renewable energy. This research highlights the critical role of EVs in stabilizing the grid and utilizing renewable energy effectively by expanding storage capacity. The optimization framework addresses key challenges in energy trading, offering a transferable methodology for broader energy storage applications. This supports the transition to a sustainable energy system by improving environmental outcomes and economic incentives.

Keywords: Electric Vehicles, Energy Grid, Energy Storages, Redispatch

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Authors: Setyarini Sri, Nursalim Agus

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Integrating critical thinking and digital based learning is one of demands in teaching English in 21st century. Child-friendly digital storytelling (CFDS) is an innovative learning model to promote young learners’ critical thinking. Therefore, this study aims to (1) investigate how child-friendly digital storytelling is implemented to promote young learners’ critical thinking in speaking English; (2) find out the benefits gained by the students in their learning based on CFDS. Classroom Action Research (CAR) took place in two cycles in which each of the cycle covered four phases namely: Planning, Acting, Observing, and Evaluating. Three classes of seventh graders were selected as the subjects of this study. Data were collected through observation, interview with some selected students as respondents, and document analysis in the form individual recorded storytelling. Sentences, phrases, words found in the transcribed data were identified and categorized based on Bloom taxonomy. The findings from the first cycle showed that the students seemed to speak critically that can be seen from the way they understood the story and related the story to their real life. Meanwhile, the result investigated from the second cycle likely indicated their higher level of critical thinking since the students spoke in English critically through comparing, questioning, analyzing, and evaluating the story by giving arguments, opinions, and comments. Such higher levels of critical thinking were also found in the students’ final project of individual recorded digital story. It is elaborated from the students’ statements in the interview who claimed CFDS offered opportunity to the students to promote their critical thinking because they comprehended the story deeply as they experienced in their real life. This learning model created good learning atmosphere and engaged the students directly so that they looked confident to retell the story in various perspectives. In term of the benefits of child-friendly digital storytelling, the students found it beneficial for some enjoyable classroom activities through watching beautiful and colorful pictures, listening to clear and good sounds, appealing moving motion and emotionally they were involved in that story. In the interview, the students also stated that child-friendly digital storytelling eased them to understand the meaning of the story as they were motivated and enthusiastic to speak in English critically.

Keywords: critical thinking, child-friendly digital storytelling, English speaking, promoting, young learners

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Authors: Vaclav Sadilek, Miroslav Vorechovsky

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The paper deals with the classical fiber bundle model of equal load sharing, sometimes referred to as the Daniels' bundle or the democratic bundle. Daniels formulated a multidimensional integral and also a recursive formula for evaluation of the strength cumulative distribution function. This paper describes three algorithms for evaluation of the recursive formula and also their implementations with source codes in high-level programming language Python. A comparison of the algorithms are provided with respect to execution time. Analysis of orders of magnitudes of addends in the recursion is also provided.

Keywords: equal load sharing, mpmath, python, strength of Daniels' bundle

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Authors: Shiva Hashemi, Azizan Marzuki, S. Kiumarsi

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In recent years, conference destinations have been highly competitive; therefore, it is necessary to know about the behaviours of conference participants such as the process of their decision-making and the assessment of perceived conference quality. A conceptual research framework based on the Theory of Planned Behaviour model is presented in this research to get better understanding factors that influence it. This research study highlights key factors presented in previous studies in which behaviour intentions of participants are affected by the quality of conference. Therefore, this study is believed to provide an idea that conference participants should be encouraged to contribute to the quality and behaviour intention of the conference.

Keywords: conference, attendees, service quality, perceives value, trust, behavioural intention.

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Authors: Boguslaw Schreyer

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In some types of wheeled robots it is important to secure starting acceleration and deceleration maxima while at the same time maintaining transversal stability. In this paper torque distribution between the front and rear wheels as well as the timing of torque application have been calculated. Both secure an optimum traction coefficient. This paper also identifies required input signals to a control unit, which controls the torque values and timing. Using a three dimensional, two mass model of a robot developed by the author a computer simulation was performed confirming the calculations presented in this paper. These calculations were also implemented and confirmed during military robot testing.

Keywords: robot dynamics, torque distribution, traction coefficient, wheeled robots

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Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

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Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

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Authors: Ammar Khader Almasri

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The software processes play a vital role for delivering a high quality software system that meets the user’s needs. There are many software development models which are used by most system developers, which can be categorized into two categories (traditional and new methodologies). Mobile applications like other desktop applications need appropriate and well-working software development process. Nevertheless, mobile applications have different features which limit their performance and efficiency like application size, mobile hardware features. Moreover, this research aims to help developers in using a standardized model for developing mobile applications.

Keywords: software development process, agile methods , moblile application development, traditional methods

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Authors: Parag Katira, Frederika Rentzeperis, Zuzanna Nowicka, Giada Fiandaca, Thomas Veith, Jack Farinhas, Noemi Andor

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Resource limitations shape the outcome of competitions between genetically heterogeneous pre-malignant cells. One example of such heterogeneity is in the ploidy (DNA content) of pre-malignant cells. A whole-genome duplication (WGD) transforms a diploid cell into a tetraploid one and has been detected in 28-56% of human cancers. If a tetraploid subclone expands, it consistently does so early in tumor evolution, when cell density is still low, and competition for nutrients is comparatively weak – an observation confirmed for several tumor types. WGD+ cells need more resources to synthesize increasing amounts of DNA, RNA, and proteins. To quantify resource limitations and how they relate to ploidy, we performed a PAN cancer analysis of WGD, PET/CT, and MRI scans. Segmentation of >20 different organs from >900 PET/CT scans were performed with MOOSE. We observed a strong correlation between organ-wide population-average estimates of Oxygen and the average ploidy of cancers growing in the respective organ (Pearson R = 0.66; P= 0.001). In-vitro experiments using near-diploid and near-tetraploid lineages derived from a breast cancer cell line supported the hypothesis that DNA content influences Glucose- and Oxygen-dependent proliferation-, death- and migration rates. To model how subpopulations with variable DNA content compete in the resource-limited environment of the human brain, we developed a stochastic state-space model of the brain (S3MB). The model discretizes the brain into voxels, whereby the state of each voxel is defined by 8+ variables that are updated over time: stiffness, Oxygen, phosphate, glucose, vasculature, dead cells, migrating cells and proliferating cells of various DNA content, and treat conditions such as radiotherapy and chemotherapy. Well-established Fokker-Planck partial differential equations govern the distribution of resources and cells across voxels. We applied S3MB on sequencing and imaging data obtained from a primary GBM patient. We performed whole genome sequencing (WGS) of four surgical specimens collected during the 1ˢᵗ and 2ⁿᵈ surgeries of the GBM and used HATCHET to quantify its clonal composition and how it changes between the two surgeries. HATCHET identified two aneuploid subpopulations of ploidy 1.98 and 2.29, respectively. The low-ploidy clone was dominant at the time of the first surgery and became even more dominant upon recurrence. MRI images were available before and after each surgery and registered to MNI space. The S3MB domain was initiated from 4mm³ voxels of the MNI space. T1 post and T2 flair scan acquired after the 1ˢᵗ surgery informed tumor cell densities per voxel. Magnetic Resonance Elastography scans and PET/CT scans informed stiffness and Glucose access per voxel. We performed a parameter search to recapitulate the GBM’s tumor cell density and ploidy composition before the 2ⁿᵈ surgery. Results suggest that the high-ploidy subpopulation had a higher Glucose-dependent proliferation rate (0.70 vs. 0.49), but a lower Glucose-dependent death rate (0.47 vs. 1.42). These differences resulted in spatial differences in the distribution of the two subpopulations. Our results contribute to a better understanding of how genomics and microenvironments interact to shape cell fate decisions and could help pave the way to therapeutic strategies that mimic prognostically favorable environments.

Keywords: tumor evolution, intra-tumor heterogeneity, whole-genome doubling, mathematical modeling

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Authors: Y. Johnson

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Study of multi-satellite formation flight systems has drawn wide attention recently due to so many potential advantages. The present work aims to model the relative motion dynamics in terms of change in classical orbital parameters between the two satellites-chief and deputy- under Earth’s oblateness effect. The required impulsive thrust control is calculated to minimize these orbital parameter changes. The formation configuration is initialized by selecting a set of orbital parameters for the chief and deputy satellites such that bounded motion is maintained for a long time in a J_2-invariant relative non-circular orbit between the satellites. The solution of J_2-modified Hill’s equations is also derived in this paper.

Keywords: satellite, formation flight, j2 effect, control

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Authors: M. Chumburidze, N. Salia, T. Namchevadze

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This work deal with case processing problems in business. The task of strategic credit requirements management of cases portfolio is discussed. The information model of credit requirements in a binary tree diagram is considered. The algorithms to solve issues of prioritizing clusters of cases in business have been investigated. An implementation of priority queues to support case management operations has been presented. The corresponding pseudo codes for the programming application have been constructed. The tools applied in this development are based on binary tree ordering algorithms, optimization theory, and business management methods.

Keywords: credit network, case portfolio, binary tree, priority queue, stack

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Authors: Raj Kishore Swain, Kamdev Sethy, Sumanta Kumar Mishra

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Selenium is an essential trace element for the chicken with a variety of biological functions like growth, fertility, immune system, hormone metabolism, and antioxidant defense systems. Selenium deficiency in chicken causes exudative diathesis, pancreatic dystrophy and nutritional muscle dystrophy of the gizzard, heart and skeletal muscle. Additionally, insufficient immunity, lowering of production ability, decreased feathering of chickens and increased embryo mortality may occur due to selenium deficiency. Nano elemental selenium, which is bright red, highly stable, soluble and of nano meter size in the redox state of zero, has high bioavailability and low toxicity due to the greater surface area, high surface activity, high catalytic efficiency and strong adsorbing ability. To assess the effect of dietary nano-Se on performance and expression of gene in Vencobb broiler birds in comparison to its inorganic form (sodium selenite), four hundred fifty day-old Vencobb broiler chicks were randomly distributed into 9 dietary treatment groups with two replicates with 25 chicks per replicate. The dietary treatments were: T1 (Control group): Basal diet; T2: Basal diet with 0.3 ppm of inorganic Se; T3: Basal diet with 0.01875 ppm of nano-Se; T4: Basal diet with 0.0375 ppm of nano-Se; T5: Basal diet with 0.075 ppm of nano-Se, T6: Basal diet with 0.15 ppm of nano-Se, T7: Basal diet with 0.3 ppm of nano-Se, T8: Basal diet with 0.60 ppm of nano-Se, T9: Basal diet with 1.20 ppm of nano-Se. Nano selenium was synthesized by mixing sodium selenite with reduced glutathione and bovine serum albumin. The experiment was carried out in two phases: starter phase (0-3 wks), finisher phase (4-5 wk) in deep litter system. The body weight at the 5th week was best observed in T4. The best feed conversion ratio at the end of 5th week was observed in T4. Erythrocytic catalase, glutathione peroxidase and superoxide dismutase activity were significantly (P < 0.05) higher in all the nano selenium treated groups at 5th week. The antibody titers (log2) against Ranikhet diseases vaccine immunization of 5th-week broiler birds were significantly higher (P < 0.05) in the treatments T4 to T7. The selenium levels in liver, breast, kidney, brain, and gizzard were significantly (P < 0.05) increased with increasing dietary nano-Se indicating higher bioavailability of nano-Se compared to inorganic Se. The real time polymer chain reaction analysis showed an increase in the expression of antioxidative gene in T4 and T7 group. Therefore, it is concluded that supplementation of nano-selenium at 0.0375 ppm over and above the basal level can improve the body weight, antioxidant enzyme activity, Se bioavailability and expression of the antioxidative gene in broiler birds.

Keywords: chicken, growth, immunity, nano selenium

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Authors: Maleh Yassine, Ezzati Abdellah

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Wireless Sensor Networks (WSNs) are currently used in different industrial and consumer applications, such as earth monitoring, health related applications, natural disaster prevention, and many other areas. Security is one of the major aspects of wireless sensor networks due to the resource limitations of sensor nodes. However, these networks are facing several threats that affect their functioning and their life. In this paper we present security attacks in wireless sensor networks, and we focus on a review and analysis of the recent Intrusion Detection schemes in WSNs.

Keywords: wireless sensor networks, security attack, denial of service, IDS, cluster-based model, signature based IDS, hybrid IDS

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Authors: Mohammad Afkhami, Ali Hassanpour, Michael Fairweather

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The work described in this paper was undertaken to gain insight into fundamental aspects of turbulent gas-particle flows with relevance to processes employed in a wide range of applications, such as oil and gas flow assurance in pipes, powder dispersion from dry powder inhalers, and particle resuspension in nuclear waste ponds, to name but a few. In particular, the influence of particle interaction and fluid phase behavior in turbulent flow on particle dispersion in a horizontal channel is investigated. The mathematical modeling technique used is based on the large eddy simulation (LES) methodology embodied in the commercial CFD code FLUENT, with flow solutions provided by this approach coupled to a second commercial code, EDEM, based on the discrete element method (DEM) which is used for the prediction of particle motion and interaction. The results generated by LES for the fluid phase have been validated against direct numerical simulations (DNS) for three different channel flows with shear Reynolds numbers, Reτ = 150, 300 and 590. Overall, the LES shows good agreement, with mean velocities and normal and shear stresses matching those of the DNS in both magnitude and position. The research work has focused on the prediction of those conditions favoring particle aggregation and deposition within turbulent flows. Simulations have been carried out to investigate the effects of particle size, density and concentration on particle agglomeration. Furthermore, particles with different surface properties have been simulated in three channel flows with different levels of flow turbulence, achieved by increasing the Reynolds number of the flow. The simulations mimic the conditions of two-phase, fluid-solid flows frequently encountered in domestic, commercial and industrial applications, for example, air conditioning and refrigeration units, heat exchangers, oil and gas suction and pressure lines. The particle size, density, surface energy and volume fractions selected are 45.6, 102 and 150 µm, 250, 1000 and 2159 kg m-3, 50, 500, and 5000 mJ m-2 and 7.84 × 10-6, 2.8 × 10-5, and 1 × 10-4, respectively; such particle properties are associated with particles found in soil, as well as metals and oxides prevalent in turbulent bounded fluid-solid flows due to erosion and corrosion of inner pipe walls. It has been found that the turbulence structure of the flow dominates the motion of the particles, creating particle-particle interactions, with most of these interactions taking place at locations close to the channel walls and in regions of high turbulence where their agglomeration is aided both by the high levels of turbulence and the high concentration of particles. A positive relationship between particle surface energy, concentration, size and density, and agglomeration was observed. Moreover, the results derived for the three Reynolds numbers considered show that the rate of agglomeration is strongly influenced for high surface energy particles by, and increases with, the intensity of the flow turbulence. In contrast, for lower surface energy particles, the rate of agglomeration diminishes with an increase in flow turbulence intensity.

Keywords: agglomeration, channel flow, DEM, LES, turbulence

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Authors: Sakshi Dhumale, Madhushree C., Amba Shetty

Abstract:

The effect of station density on the geostatistical prediction of groundwater levels is of critical importance to ensure accurate and reliable predictions. Monitoring station density directly impacts the accuracy and reliability of geostatistical predictions by influencing the model's ability to capture localized variations and small-scale features in groundwater levels. This is particularly crucial in regions with complex hydrogeological conditions and significant spatial heterogeneity. Insufficient station density can result in larger prediction uncertainties, as the model may struggle to adequately represent the spatial variability and correlation patterns of the data. On the other hand, an optimal distribution of monitoring stations enables effective coverage of the study area and captures the spatial variability of groundwater levels more comprehensively. In this study, we investigate the effect of station density on the predictive performance of groundwater levels using the geostatistical technique of Ordinary Kriging. The research utilizes groundwater level data collected from 121 observation wells within the semi-arid Berambadi watershed, gathered over a six-year period (2010-2015) from the Indian Institute of Science (IISc), Bengaluru. The dataset is partitioned into seven subsets representing varying sampling densities, ranging from 15% (12 wells) to 100% (121 wells) of the total well network. The results obtained from different monitoring networks are compared against the existing groundwater monitoring network established by the Central Ground Water Board (CGWB). The findings of this study demonstrate that higher station densities significantly enhance the accuracy of geostatistical predictions for groundwater levels. The increased number of monitoring stations enables improved interpolation accuracy and captures finer-scale variations in groundwater levels. These results shed light on the relationship between station density and the geostatistical prediction of groundwater levels, emphasizing the importance of appropriate station densities to ensure accurate and reliable predictions. The insights gained from this study have practical implications for designing and optimizing monitoring networks, facilitating effective groundwater level assessments, and enabling sustainable management of groundwater resources.

Keywords: station density, geostatistical prediction, groundwater levels, monitoring networks, interpolation accuracy, spatial variability

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Authors: Erekle Magradze, Davit Soselia, Levan Shughliashvili, Irakli Koberidze, Shota Tsiskaridze, Victor Kakhniashvili, Tamar Chaghiashvili

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Since the beginning of active publishing activity in Georgia, voluminous printed material has been accumulated, the digitization of which is an important task. Digitized materials will be available to the audience, and it will be possible to find text in them and conduct various factual research. Digitizing scanned documents means scanning documents, extracting text from the scanned documents, and processing the text into a corresponding language model to detect inaccuracies and grammatical errors. Implementing these stages requires a unified, scalable, and automated platform, where the digital service developed for each stage will perform the task assigned to it; at the same time, it will be possible to develop these services dynamically so that there is no interruption in the work of the platform.

Keywords: NLP, OCR, BERT, Kubernetes, transformers

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Authors: S. Lecheb, A. Nour, A. Chellil, H. Mechakra, A. Zeggane, H. Kebir

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In this work, repaired crack in 6061-T6 aluminum plate with composite patches presented, firstly we determine the displacement, strain, and stress, also the first six mode shape of the plate, secondly we took the same model adding central crack initiation, which is located in the center of the plate, its size vary from 20 mm to 60 mm and we compare the first results with second. Thirdly, we repair various cracks with the composite patch (carbon/epoxy) and for (2 layers, 4 layers). Finally, the comparison of stress, strain, displacement and six first natural frequencies between un-cracked specimen, crack propagation and composite patch repair.

Keywords: composite patch repair, crack growth, aluminum alloy plate, stress

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Authors: Gaurav Gupta, Jitendra Mahakud

Abstract:

This study focuses on the significance of internal financing constraints on the determination of corporate fixed investments in the case of Indian manufacturing companies. Financing constraints companies which have less internal fund or retained earnings face more transaction and borrowing costs due to imperfections in the capital market. The period of study is 1999-2000 to 2013-2014 and we consider 618 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test, and Hausman test results conclude the suitability of the fixed effect model for the estimation. The cash flow and liquidity of the company have been used as the proxies for the internal financial constraints. In accordance with various theories of corporate investments, we consider other firm specific variable like firm age, firm size, profitability, sales and leverage as the control variables in the model. From the econometric analysis, we find internal cash flow and liquidity have the significant and positive impact on the corporate investments. The variables like cost of capital, sales growth and growth opportunities are found to be significantly determining the corporate investments in India, which is consistent with the neoclassical, accelerator and Tobin’s q theory of corporate investment. To check the robustness of results, we divided the sample on the basis of cash flow and liquidity. Firms having cash flow greater than zero are put under one group, and firms with cash flow less than zero are put under another group. Also, the firms are divided on the basis of liquidity following the same approach. We find that the results are robust to both types of companies having positive and negative cash flow and liquidity. The results for other variables are also in the same line as we find for the whole sample. These findings confirm that internal financing constraints play a significant role for determination of corporate investment in India. The findings of this study have the implications for the corporate managers to focus on the projects having higher expected cash inflows to avoid the financing constraints. Apart from that, they should also maintain adequate liquidity to minimize the external financing costs.

Keywords: cash flow, corporate investment, financing constraints, panel data method

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Authors: Suzan Duygu Bedir Erişti

Abstract:

The present study tried to make a general evaluation of the dissertations conducted in the last decade in the field of art education in the Department of Fine Arts Education in the Institutes of Education Sciences in Turkey. In the study, most of the universities which involved an Institute of Education Sciences within their bodies in Turkey were reached. As a result, a total of a hundred dissertations conducted in the departments of Fine Arts Education at several universities (Anadolu, Gazi, Ankara, Marmara, Dokuz Eylul, Ondokuz Mayıs, Selcuk and Necmettin Erbakan) were determined via the open access systems of universities as well as via the Thesis Search System of Higher Education Council. Most of the dissertations were reached via the latter system, and in cases of failure, the dissertations were reached via the former system. Consequently, most of the dissertations which did not have any access restriction and which had appropriate content were reached. The dissertations reached were examined based on document analysis in terms of their research topics, research paradigms, contents, purposes, methodologies, data collection tools, and analysis techniques. The dissertations conducted in institutes of Education Sciences could be said to have demonstrated a development, especially in recent years with respect to their qualities. It was also found that a great majority of the dissertations were carried out at Gazi University and Marmara University and that a similar number of dissertations were conducted in other universities. When all the dissertations were taken into account, in general, they were found to differ a lot in their subject areas. In most of the dissertations, the quantitative paradigm was adopted, while especially in recent years, more importance has been given to methods based on the qualitative paradigm. In addition, most of the dissertations conducted with quantitative paradigm were structured based on the general survey model and experimental research model. In terms of statistical techniques, university-focused approaches were used. In some universities, advanced statistical techniques were applied, while in some other universities, there was a moderate use of statistical techniques. Most of the studies produced results generalizable to the levels of postgraduate education and elementary school education. The studies were generally structured in face-to-face teaching processes, while some of them were designed in environments which did not include results generalizable to the face-to-face education system. In the present study, it was seen that the dissertations conducted in the departments of Fine Arts Education at the Institutes of Education Sciences in Turkey did not involve application-based approaches which included art-based or visual research in terms of either research topic or methodology.

Keywords: fine arts education, dissertations, evaluation of dissertations, research trends in fine arts education

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Authors: Nathaniel Bayode Eniolorunda, Murtala Abubakar Gada, Sheikh Danjuma Abubakar

Abstract:

The challenge of erosion in the study area is persistent, suggesting the need for a better understanding of the mechanisms that drive it. Thus, the study evolved a predictive erosion model (RUSLE_Sok), deploying Remote Sensing (RS) and Geographical Information System (GIS) tools. The nature and pattern of the factors of erosion were characterized, while soil losses were quantified. Factors’ impacts were also measured, and the morphometry of gullies was described. Data on the five factors of RUSLE and distances to settlements, rivers and roads (K, R, LS, P, C, DS DRd and DRv) were combined and processed following standard RS and GIS algorithms. Harmonized World Soil Data (HWSD), Shuttle Radar Topographical Mission (SRTM) image, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), Sentinel-2 image accessed and processed within the Google Earth Engine, road network and settlements were the data combined and calibrated into the factors for erosion modeling. A gully morphometric study was conducted at some purposively selected sites. Factors of soil erosion showed low, moderate, to high patterns. Soil losses ranged from 0 to 32.81 tons/ha/year, classified into low (97.6%), moderate (0.2%), severe (1.1%) and very severe (1.05%) forms. The multiple regression analysis shows that factors statistically significantly predicted soil loss, F (8, 153) = 55.663, p < .0005. Except for the C-Factor with a negative coefficient, all other factors were positive, with contributions in the order of LS>C>R>P>DRv>K>DS>DRd. Gullies are generally from less than 100m to about 3km in length. Average minimum and maximum depths at gully heads are 0.6 and 1.2m, while those at mid-stream are 1 and 1.9m, respectively. The minimum downstream depth is 1.3m, while that for the maximum is 4.7m. Deeper gullies exist in proximity to rivers. With minimum and maximum gully elevation values ranging between 229 and 338m and an average slope of about 3.2%, the study area is relatively flat. The study concluded that major erosion influencers in the study area are topography and vegetation cover and that the RUSLE_Sok well predicted soil loss more effectively than ordinary RUSLE. The adoption of conservation measures such as tree planting and contour ploughing on sloppy farmlands was recommended.

Keywords: RUSLE_Sok, Sokoto, google earth engine, sentinel-2, erosion

Procedia PDF Downloads 76