Search results for: computational methods

Authors: Majed Zobairy, Payam Mohammadpanahi

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Introduction: Skill movement education is one of extremely important duty for sport coaches and sport teachers. Researchers have done lots of studies in this filed to gain the best methodology in movement learning. One of the essential aspects in skill movement education is observational learning. Observational learning, or learning by watching demonstrations, has been characterized as one of the most important methods by which people learn variety of skill and behaviours.The purpose of this study was determined the effect of observational practice on the volleyball service learning with emphasis on the Role of Self–Efficacy. Methods: The Sample consisted of100 male students was assigned accessible sampling technique and homogeneous manner with emphasis on the Role of Self–Efficacy level to 4 groups. The first group performed physical training, the second group performed observational practice task, the third practiced physically and observationally and the fourth group served as the control group. The experimental groups practiced in a one day acquisition and performed the retention task, after 72 hours. Kolmogorov-Smirnov test and independent t-test were used for Statistical analyses. Results and Discussion: Results shows that observation practice task group can significantly improve volleyball services skills acquisition (T=7.73). Also mixed group (physically and observationally) is significantly better than control group regarding to volleyball services skills acquisition (T=7.04). Conclusion: Results have shown observation practice task group and mixed group are significantly better than control group in acquisition test. The present results are in line with previous studies, suggesting that observation learning can improve performance. On the other hand, results shows that self-efficacy level significantly effect on acquisition movement skill. In other words, high self-efficacy is important factor in skill learning level in volleyball service.

Keywords: observational practice, volleyball service, self–efficacy, sport science

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Authors: Mohamed Razi Nalim, Shahrzad Ghadiri

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With current concerns regarding global warming, demand for a society with greater environmental awareness significantly increases. With gradual development in hybrid and electric vehicles and the availability of renewable energy resources, increasing efficiency in fossil fuel and combustion engines seems a faster solution toward sustainability and reducing greenhouse gas emissions. This paper aims to provide a comprehensive review of recent progress in wave rotor combustor, one of the combustion concepts with considerable potential to improve power output and emission standards. A wave rotor is an oscillatory flow device that uses the unsteady gas dynamic concept to transfer energy by generating pressure waves. From a thermodynamic point of view, unlike conventional positive-displacement piston engines which follow the Brayton cycle, wave rotors offer higher cycle efficiency due to pressure gain during the combustion process based on the Humphrey cycle. First, the paper covers all recent and ongoing computational and experimental studies around the world with a quick look at the milestones in the history of wave rotor development. Second, the main similarity and differences in the ignition system of the wave rotor with piston engines are considered. Also, the comparison is made with another pressure gain device, rotating detonation engines. Next, the main challenges and research needs for wave rotor combustor commercialization are discussed.

Keywords: wave rotor combustor, unsteady gas dynamic, pre-chamber jet ignition, pressure gain combustion, constant-volume combustion

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Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

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Authors: Dalya Markovich

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In the last decade art-educators strive to integrate critical pedagogy within the art classroom. Critical pedagogy aims to deconstruct the oppressive social reality and the false consciousness in which learners from both privileged and underprivileged groups are caught. Understanding oppression as a product of socio-political conditions seeks to instigate processes of change anchored in the student's views. Yet, growing empirical evidence show that these efforts often has resulted in art projects in which art teachers play an active role in the process of critical teaching, while the students remain passive listeners. In this common scenario, the teachers/artists become authoritarian moral guides of critical thinking and acting, while the students are often found to be indifferent or play along to satisfy the teachers'/artists aspirations. These responses indicate that the message of critical pedagogy – transforming the students' way of thinking and acting – mostly do not fulfill its emancipation goals. The study analyses the critical praxis embedded in new art projects and their influence on the participants. This type of projects replaces the individual producer with a collaborative work; switch the finite work with an ongoing project; and transforms the passive learner to an engaged co-producer. The research delves into the pedagogical framework of two of these art projects by using qualitative methods. In-depth interviews were conducted with 4 of the projects' initiator and managers, in order to access understandings of the art projects goals and pedagogical methods. Field work included 4 participant observation (two in each project) during social encounters in the project's settings, focusing on how critical thinking is enacted (or not) by the participants. The analysis exposes how the new art projects avoid the prepackaged "critical" assumptions and praxis, thus turning the participants from passive carriers of critical thinking to agents that actively use criticism. Findings invite researchers to explore new avenues for understanding critical pedagogy and developing various ways to implement critical pedagogy during art education, in view of the growing need of critical thinking and acting in school/society.

Keywords: critical pedagogy, education through art, collaborative work, agency

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Authors: Hilal Naimi, Amelbahahouda Adamou-Mitiche, Lahcene Mitiche

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The main problem in the area of medical imaging has been image denoising. The most defying for image denoising is to secure data carrying structures like surfaces and edges in order to achieve good visual quality. Different algorithms with different denoising performances have been proposed in previous decades. More recently, models focused on deep learning have shown a great promise to outperform all traditional approaches. However, these techniques are limited to the necessity of large sample size training and high computational costs. This research proposes a denoising approach basing on LDTCWT (Lifting Dual Tree Complex Wavelet Transform) using Hybrid Thresholding with Wiener filter to enhance the quality image. This research describes the LDTCWT as a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). To develop this approach, a hybrid thresholding function is modeled by integrating the Wiener filter into the thresholding function.

Keywords: lifting wavelet transform, image denoising, dual tree complex wavelet transform, wavelet shrinkage, wiener filter

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Authors: S. Ben-Shabat, T. Turgeman, O. Leubinski, N. Roth-Bejerano, V. Kagan-Zur, Y. Sitrit

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The ectomycorrhizal (ECM) desert truffle Terfezia boudieri produces edible fruit bodies and forms symbiosis with its host plant Helianthemum sessiliflorum (Cistaceae) in the Negev desert of Israel. The symbiosis is vital for both partners' survival under desert conditions. Under desert habitat conditions, ECMs must form symbiosis before entering the dry season. To secure a successful encounter, in the course of evolution, both partners have responded by evolving special signals exchange that facilitates recognition. Members of the Cistaceae family serve as host plants for many important truffles. Conceivably, during evolution a common molecule present in Cistaceae plants was recruited to facilitate successful encounter with ectomycorrhizas. Arbuscular vesicular fungi (AM) are promiscuous in host preferences, in contrast, ECM fungi show specificity to host plants. Accordingly, we hypothesize that H. sessiliflorum secretes a chemotrophic-signaling, which is common to plants hosting ECM fungi belonging to the Pezizales. However, thus far no signaling molecules have been identified in ECM fungi. We developed a bioassay for chemotrophic activity. Fractionation of root exudates revealed a substance with chemotrophic activity and molecular mass of 534. Following the above concept, screening the transcriptome of Terfezia, grown under chemoattraction, discovered genes showing high homology to G proteins-coupled receptors of plant pathogens involved in positive chemotaxis and chemotaxis suppression. This study aimed to identify the active molecule using analytical methods (LC-MS, NMR etc.). This should contribute to our understanding of how ECM fungi communicate with their hosts in the rhizosphere. In line with the ability of Terfezia to form also endomycorrhizal symbiosis like AM fungi, analysis of the mechanisms may likewise be applicable to AM fungi. Developing methods to manipulate fungal growth by the chemoattractant can open new ways to improve inoculation of plants.

Keywords: chemotrophic signal, Helianthemum sessiliflorum, Terfezia boudieri, ECM

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

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Authors: Maria Amodeo, Pasquale Arpaia, Marco Buzio, Vincenzo Di Capua, Francesco Donnarumma

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Different deep neural network architectures have been compared and tested to predict magnetic hysteresis in the context of pulsed electromagnets for experimental physics applications. Modelling quasi-static or dynamic major and especially minor hysteresis loops is one of the most challenging topics for computational magnetism. Recent attempts at mathematical prediction in this context using Preisach models could not attain better than percent-level accuracy. Hence, this work explores neural network approaches and shows that the architecture that best fits the measured magnetic field behaviour, including the effects of hysteresis and eddy currents, is the nonlinear autoregressive exogenous neural network (NARX) model. This architecture aims to achieve a relative RMSE of the order of a few 100 ppm for complex magnetic field cycling, including arbitrary sequences of pseudo-random high field and low field cycles. The NARX-based architecture is compared with the state-of-the-art, showing better performance than the classical operator-based and differential models, and is tested on a reference quadrupole magnetic lens used for CERN particle beams, chosen as a case study. The training and test datasets are a representative example of real-world magnet operation; this makes the good result obtained very promising for future applications in this context.

Keywords: deep neural network, magnetic modelling, measurement and empirical software engineering, NARX

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Authors: Ehsan Pegah, Huabei Liu

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Characterizing the deformation properties of fill materials in a wide stress range always has been an important issue in geotechnical engineering. The hyperbolic Duncan-Chang model is a very popular model of stress-strain relationship that captures the nonlinear deformation of granular geomaterials in a very tractable manner. It consists of a particular set of the model parameters, which are generally measured from an extensive series of laboratory triaxial tests. This practice is both time-consuming and costly, especially in large projects. In addition, undesired effects caused by soil disturbance during the sampling procedure also may yield a large degree of uncertainty in the results. Accordingly, non-invasive geophysical seismic approaches may be utilized as the appropriate alternative surveys for measuring the model parameters based on the seismic wave velocities. To this end, the conventional seismic refraction profiles were carried out in the test sites with the granular fill materials to collect the seismic waves information. The acquired shot gathers are processed, from which the P- and S-wave velocities can be derived. The P-wave velocities are extracted from the Seismic Refraction Tomography (SRT) technique while S-wave velocities are obtained by the Multichannel Analysis of Surface Waves (MASW) method. The velocity values were then utilized with the equations resulting from the rigorous theories of elasticity and soil mechanics to evaluate the Duncan-Chang model parameters. The derived parameters were finally compared with those from laboratory tests to validate the reliability of the results. The findings of this study may confidently serve as the useful references for determination of nonlinear deformation parameters of granular fill geomaterials. Those are environmentally friendly and quite economic, which can yield accurate results under the actual in-situ conditions using the surface seismic methods.

Keywords: Duncan-Chang deformation parameters, granular fill materials, seismic waves velocity, multichannel analysis of surface waves, seismic refraction tomography

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Authors: Syed Muhammad Awais Tahir, Syed Hossein Raza Hamdani

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In the last two years, there has been a substantial increase in the rate of satellite launches. To keep up with the technology, it is imperative that the launch cost must be made affordable, especially in developing and underdeveloped countries. Launch cost is directly affected by the launch vehicle’s aerodynamic performance. Pegasus-XL SLV (Satellite Launch Vehicle) has been serving as a commercial SLV for the last 26 years, commencing its commercial flight operation from the six operational sites all around the US and Europe, and the Marshal Islands. Aerodynamic heating and drag contribute largely to Pegasus’s flight performance. The objective of this study is to reduce the aerodynamic heating and drag on Pegasus’s body significantly for supersonic and hypersonic flight regimes. Aerodynamic data for Pegasus’s first flight has been validated through CFD (Computational Fluid Dynamics), and then drag and aerodynamic heating is reduced by using a combination of a forward-facing cylindrical spike and a conical aero-disk at the actual operational flight conditions. CFD analysis using ANSYS fluent will be carried out for Mach no. ranges from 0.83 to 7.8, and AoA (Angle of Attack) ranges from -4 to +24 degrees for both simple and spiked-configuration, and then the comparison will be drawn using a variety of graphs and contours. Expected drag reduction for supersonic flight is to be around 15% to 25%, and for hypersonic flight is to be around 30% to 50%, especially for AoA < 15⁰. A 5% to 10% reduction in aerodynamic heating is expected to be achieved for hypersonic regions. In conclusion, the aerodynamic performance of air-launched Pegasus-XL SLV can be further enhanced, leading to its optimal fuel usage to achieve a more economical orbital flight.

Keywords: aerodynamics, pegasus-XL, drag reduction, aerodynamic heating, satellite launch vehicle, SLV, spike, aero-disk

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Authors: Olakanmi Oladayo Olufemi, Bamifewe Olusegun James, Badmus Yaya Opeyemi, Adegoke Kayode

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The wireless sensor network (WSN) has made a significant contribution to the emergence of various intelligent services or cloud-based applications. Most of the time, these data are stored on a cloud platform for efficient management and sharing among different services or users. However, the sensitivity of the data makes them prone to various confidentiality and performance-related attacks during and after harvesting. Various security schemes have been developed to ensure the integrity and confidentiality of the WSNs' data. However, their specificity towards particular attacks and the resource constraint and heterogeneity of WSNs make most of these schemes imperfect. In this paper, we propose a secure variance-aware routing and authentication scheme with two-tier verification to collect, share, and manage WSN data. The scheme is capable of classifying WSN into different subnets, detecting any attempt of wormhole and black hole attack during harvesting, and enforcing access control on the harvested data stored in the cloud. The results of the analysis showed that the proposed scheme has more security functionalities than other related schemes, solves most of the WSNs and cloud security issues, prevents wormhole and black hole attacks, identifies the attackers during data harvesting, and enforces access control on the harvested data stored in the cloud at low computational, storage, and communication overheads.

Keywords: data block, heterogeneous IoT network, data harvesting, wormhole attack, blackhole attack access control

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Authors: Lan Cheng, Harry Qin, Yang Wang

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Background: COVID-19 has induced the largest digital learning experiment in history. There is also emerging research evidence that students have paid a high cost of learning loss from virtual learning. University-wide survey results demonstrate that digital learning remains difficult for students who struggle with learning challenges, isolation, or a lack of resources. Large-scale efforts are therefore increasingly utilized for digital education. To better prepare students in higher education for this grand scientific and technological transformation, STEM education has been prioritized and promoted as a strategic imperative in the ongoing curriculum reform essential for unfinished learning needs and whole-person development. Building upon five key elements identified in the STEM education literature: Problem-based Learning, Community and Belonging, Technology Skills, Personalization of Learning, Connection to the External Community, this case study explores the potential of pedagogical innovation that integrates computational and experimental methodologies to support, enrich, and navigate STEM education. Objectives: The goal of this case study is to create a high-fidelity prototype design for STEM education with knowledge transfer technology that contains a Cooperative Multi-Agent System (CMAS), which has the objectives of (1) conduct assessment to reveal a virtual learning mechanism and establish strategies to facilitate scientific learning engagement, accessibility, and connection within and beyond university setting, (2) explore and validate an interactional co-creation approach embedded in project-based learning activities under the STEM learning context, which is being transformed by both digital technology and student behavior change,(3) formulate and implement the STEM-oriented campaign to guide learning network mapping, mitigate the loss of learning, enhance the learning experience, scale-up inclusive participation. Methods: This study applied a case study strategy and a methodology informed by Social Network Analysis Theory within a cross-disciplinary communication paradigm (students, peers, educators). Knowledge transfer technology is introduced to address learning challenges and to increase the efficiency of Reinforcement Learning (RL) algorithms. A co-creation learning framework was identified and investigated in a context-specific way with a learning analytic tool designed in this study. Findings: The result shows that (1) CMAS-empowered learning support reduced students’ confusion, difficulties, and gaps during problem-solving scenarios while increasing learner capacity empowerment, (2) The co-creation learning phenomenon have examined through the lens of the campaign and reveals that an interactive virtual learning environment fosters students to navigate scientific challenge independently and collaboratively, (3) The deliverables brought from the STEM educational campaign provide a methodological framework both within the context of the curriculum design and external community engagement application. Conclusion: This study brings a holistic and coherent pedagogy to cultivates students’ interest in STEM and develop them a knowledge base to integrate and apply knowledge across different STEM disciplines. Through the co-designing and cross-disciplinary educational content and campaign promotion, findings suggest factors to empower evidence-based learning practice while also piloting and tracking the impact of the scholastic value of co-creation under the dynamic learning environment. The data nested under the knowledge transfer technology situates learners’ scientific journey and could pave the way for theoretical advancement and broader scientific enervators within larger datasets, projects, and communities.

Keywords: co-creation, cross-disciplinary, knowledge transfer, STEM education, social network analysis

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Authors: Tran Ich Thinh, Nguyen Manh Cuong

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Free vibrations of partial fluid-filled composite truncated conical shells are investigated using the Dynamic Stiffness Method (DSM) or Continuous Element Method (CEM) based on the First Order Shear Deformation Theory (FSDT) and non-viscous incompressible fluid equations. Numerical examples are given for analyzing natural frequencies and harmonic responses of clamped-free conical shells partially and completely filled with fluid. To compare with the theoretical results, detailed experimental results have been obtained on the free vibration of a clamped-free conical shells partially filled with water by using a multi-vibration measuring machine (DEWEBOOK-DASYLab 5.61.10). Three glass fiber/polyester composite truncated cones with the radius of the larger end 285 mm, thickness 2 mm, and the cone lengths along the generators are 285 mm, 427.5 mm and 570 mm with the semi-vertex angles 27, 14 and 9 degrees respectively were used, and the filling ratio of the contained water was 0, 0.25, 0.50, 0.75 and 1.0. The results calculated by proposed computational model for studied composite conical shells are in good agreement with experiments. Obtained results indicate that the fluid filling can reduce significantly the natural frequencies of composite conical shells. Parametric studies including circumferential wave number, fluid depth and cone angles are carried out.

Keywords: dynamic stiffness method, experimental study, free vibration, fluid-shell interaction, glass fiber/polyester composite conical shell

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Authors: Zaoui Ismahene, Bahri Sidi Mohamed, Abbassa Nadira

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Diabetic Retinopathy (DR) is a leading cause of vision impairment and blindness among individuals with diabetes. Early diagnosis is crucial for effective treatment, yet current diagnostic methods rely heavily on manual analysis of retinal images, which can be time-consuming and prone to subjectivity. This research proposes an automated system for the detection of DR using Jacobi wavelet-based feature extraction combined with Support Vector Machines (SVM) for classification. The integration of wavelet analysis with machine learning techniques aims to improve the accuracy, efficiency, and reliability of DR diagnosis. In this study, retinal images are preprocessed through normalization, resizing, and noise reduction to enhance the quality of the images. The Jacobi wavelet transform is then applied to extract both global and local features, effectively capturing subtle variations in retinal images that are indicative of DR. These extracted features are fed into an SVM classifier, known for its robustness in handling high-dimensional data and its ability to achieve high classification accuracy. The SVM classifier is optimized using parameter tuning to improve performance. The proposed methodology is evaluated using a comprehensive dataset of retinal images, encompassing a range of DR severity levels. The results show that the proposed system outperforms traditional wavelet-based methods, demonstrating significantly higher accuracy, sensitivity, and specificity in detecting DR. By leveraging the discriminative power of Jacobi wavelet features and the robustness of SVM, the system provides a promising solution for the automatic detection of DR, which could assist ophthalmologists in early diagnosis and intervention, ultimately improving patient outcomes. This research highlights the potential of combining wavelet-based image processing with machine learning for advancing automated medical diagnostics.

Keywords: iabetic retinopathy (DR), Jacobi wavelets, machine learning, feature extraction, classification

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Authors: M. Lobzhanidze, N. Damenia

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The article analyzes the current structural changes in the economy of Georgia, liberalization and integration processes of the economy. In accordance with this analysis, the peculiarities and the problems of youth employment are revealed. In the paper, the Georgian labor market and its contradictions are studied. Based on the analysis of materials, the socio-economic losses caused by the long-term and mass unemployment of young people are revealed, the objective and subjective circumstances of getting higher education are studied. The youth employment and unemployment rates are analyzed. Based on the research, the factors that increase unemployment are identified. According to the analysis of the youth employment, it has appeared that the unemployment share in the number of economically active population has increased in the younger age group. It demonstrates the high requirements of the labour market in terms of the quality of the workforce. Also, it is highlighted that young people are exposed to a highly paid job. The following research methods are applied in the presented paper: statistical (selection, grouping, observation, trend, etc.) and qualitative research (in-depth interview), as well as analysis, induction and comparison methods. The article presents the data by the National Statistics Office of Georgia and the Ministry of Agriculture of Georgia, policy documents of the Parliament of Georgia, scientific papers by Georgian and foreign scientists, analytical reports, publications and EU research materials on similar issues. The work estimates the students and graduates employment problems existing in the state development strategy and priorities. The measures to overcome the challenges are defined. The article describes the mechanisms of state regulation of youth employment and the ways of improving this regulatory base. As for major findings, it should be highlighted that the main problems are: lack of experience and incompatibility of youth qualification with the requirements of the labor market. Accordingly, it is concluded that the unemployment rate of young people in Georgia is increasing.

Keywords: migration of youth, youth employment, migration management, youth employment and unemployment

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Authors: M. Sasajima, M. Watanabe, T. Yamaguchi Y. Kurosawa, Y. Koike

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In very narrow pathways, the speed of sound propagation and the phase of sound waves change due to the air viscosity. We have developed a new Finite Element Method (FEM) that includes the effects of air viscosity for modeling a narrow sound pathway. This method is developed as an extension of the existing FEM for porous sound-absorbing materials. The numerical calculation results for several three-dimensional slit models using the proposed FEM are validated against existing calculation methods.

Keywords: simulation, FEM, air viscosity, slit

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Authors: Nahid Hassanshahi, Ayoub Karimi-Jashni, Nasser Talebbeydokhti

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Due to the economic and environmental benefits of producing less waste, the US Environmental Protection Agency (EPA) introduces source reduction as one of the most important means to deal with the problems caused by increased landfills and pollution. Waste reduction involves all waste management methods, including source reduction, recycling, and composting, which reduce waste flow to landfills or other disposal facilities. Source reduction of waste can be studied from two perspectives: avoiding waste production, or reducing per capita waste production, and waste deviation that indicates the reduction of waste transfer to landfills. The present paper has investigated home composting as a managerial solution for reduction of waste transfer to landfills. Home composting has many benefits. The use of household waste for the production of compost will result in a much smaller amount of waste being sent to landfills, which in turn will reduce the costs of waste collection, transportation and burial. Reducing the volume of waste for disposal and using them for the production of compost and plant fertilizer might help to recycle the material in a shorter time and to use them effectively in order to preserve the environment and reduce contamination. Producing compost in a home-based manner requires very small piece of land for preparation and recycling compared with other methods. The final product of home-made compost is valuable and helps to grow crops and garden plants. It is also used for modifying the soil structure and maintaining its moisture. The food that is transferred to landfills will spoil and produce leachate after a while. It will also release methane and greenhouse gases. But, composting these materials at home is the best way to manage degradable materials, use them efficiently and reduce environmental pollution. Studies have shown that the benefits of the sale of produced compost and the reduced costs of collecting, transporting, and burying waste can well be responsive to the costs of purchasing home compost machine and the cost of related trainings. Moreover, the process of producing home compost may be profitable within 4 to 5 years and as a result, it will have a major role in reducing waste management.

Keywords: compost, home compost, reducing waste, waste management

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Authors: Remya Radhakrishnan, Hema Perinbanathan, Anukriti Rath, Reshmi Ramachandran, Rohith Thazhathuvetil Sasindrababu, Maria Karizhenskaia

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Childhood adversities have lasting effects on health and well-being. This abstract explores the connection between adverse childhood experiences (ACEs) and health consequences, including substance abuse and obesity. Understanding the impact of childhood trauma and emphasizing the importance of culturally sensitive treatments and focused interventions help to mitigate these effects. Research consistently shows a strong link between ACEs and poor health outcomes. Our team conducted a comprehensive literature review of depression and anxiety in Canadian children and youth, exploring diverse treatment methods, including medical, psychotherapy, and alternative therapies like art and music therapy. We searched Medline, Google Scholar, and St. Lawrence College Library. Only original research papers, published between 2012 and 2023, peer-reviewed, and reporting on childhood adversities on health and its treatment methods in children and youth in Canada were considered. We focused on their significance in treating depression and anxiety. According to the study's findings, the prevalence of adverse childhood experiences (ACEs) is still a significant concern. In Canada, 40% of people report having had multiple ACEs, and 78% report having had at least one ACE, highlighting the persistence of childhood adversity and indicating that the issue is unlikely to fade off in the near future. Likewise, findings revealed that individuals who experienced abuse, neglect, or violence during childhood are likelier to engage in harmful behaviors like polydrug use, suicidal ideation, and victimization and suffer from mental health problems such as depression and post-traumatic stress disorder (PTSD).

Keywords: adverse childhood experiences (ACEs), obesity, post-traumatic stress disorder (PTSD), resilience, substance abuse, trauma-informed care

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Authors: S. K. Fasogbon, O. E. Oguegbu

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Pasteurization is one of the most important steps in the preservation of beer products, which improves its shelf life by inactivating almost all the spoilage organisms present in it. However, there is no gain saying the fact that it is always difficult to determine the slowest heating zone, the temperature profile and pasteurization units inside bottled beer during pasteurization, hence there had been significant experimental and ANSYS fluent approaches on the problem. This work now developed Computational fluid dynamics model using COMSOL Multiphysics. The model was simulated to determine the slowest heating zone, temperature profile and pasteurization units inside the bottled beer during the pasteurization process. The results of the simulation were compared with the existing data in the literature. The results showed that, the location and size of the slowest heating zone is dependent on the time-temperature combination of each zone. The results also showed that the temperature profile of the bottled beer was found to be affected by the natural convection resulting from variation in density during pasteurization process and that the pasteurization unit increases with time subject to the temperature reached by the beer. Although the results of this work agreed with literatures in the aspects of slowest heating zone and temperature profiles, the results of pasteurization unit however did not agree. It was suspected that this must have been greatly affected by the bottle geometry, specific heat capacity and density of the beer in question. The work concludes that for effective pasteurization to be achieved, there is a need to optimize the spray water temperature and the time spent by the bottled product in each of the pasteurization zones.

Keywords: modeling, heat transfer, temperature profile, pasteurization process, bottled beer

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Authors: Unsain Dianne, Roussel Audrey, Goude Gwenaëlle, Magniez Pierre, Storå Jan

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This paper aims to investigate the changes in husbandry practices and meat consumption during the transition from the Medieval Climate Anomaly to the Little Ice Age in the South of France. More precisely, we will investigate breeding strategies, animal size and health status, carcass exploitation strategies, and the impact of socioeconomic status on human-environment interactions. For that purpose, we will analyze faunal remains from ten sites equally distributed between the two periods. Those include consumers from different socio-economic backgrounds (peasants, city dwellers, soldiers, lords, and the Popes). The research will employ different methods used in zooarchaeology: comparative anatomy, biometry, pathologies analyses, traceology, and utility indices, as well as experimental archaeology, to reconstruct and understand the changes in animal breeding and consumption practices. Their analysis will allow the determination of modifications in the animal production chain, with the composition of the flocks (species, size), their management (age, sex, health status), culinary practices (strategies for the exploitation of carcasses, cooking, tastes) or the importance of trade (butchers, sales of processed animal products). The focus will also be on the social extraction of consumers. The aim will be to determine whether climate change has had a greater impact on the most modest groups (such as peasants), whether the consequences have been global and have also affected the highest levels of society, or whether the social and economic factors have been sufficient to balance out the climatic hazards, leading to no significant changes. This study will contribute to our understanding of the impact of climate change on breeding and consumption strategies in medieval society from a historical and social point of view. It combines various research methods to provide a comprehensive analysis of the changes in human-animal interactions during different climatic periods.

Keywords: archaeology, animal economy, cooking, husbandry practices, climate change, France

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Authors: Abdelkader Elhanaoui, Mhamed Hadji, Rachid Skouri, Said Agounad

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The purpose of this paper is to study the phenomenon of acoustic scattering by using a new method. The signal processing (Fast Fourier Transform FFT Inverse Fast Fourier Transform iFFT and BESSEL functions) is widely applied to obtain information with high precision accuracy. Signal processing has a wider implementation in general-purpose pro-cessors. Our interest was focused on the use of FPGAs (Field-Programmable Gate Ar-rays) in order to minimize the computational complexity in single processor architecture, then be accelerated on FPGA and meet real-time and energy efficiency requirements. Gen-eral-purpose processors are not efficient for signal processing. We implemented the acous-tic backscattered signal processing model on the Altera DE-SOC board and compared it to Odroid xu4. By comparison, the computing latency of Odroid xu4 and FPGA is 60 sec-onds and 3 seconds, respectively. The detailed SoC FPGA-based system has shown that acoustic spectra are performed up to 20 times faster than the Odroid xu4 implementation. FPGA-based system of processing algorithms is realized with an absolute error of about 10⁻³. This study underlines the increasing importance of embedded systems in underwater acoustics, especially in non-destructive testing. It is possible to obtain information related to the detection and characterization of submerged cells. So we have achieved good exper-imental results in real-time and energy efficiency.

Keywords: DE1 FPGA, acoustic scattering, form function, signal processing, non-destructive testing

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Authors: Kerry Hull, Mark Wright

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This paper brings light to ethnobotanical medicines used by the Maya of Belize to treat snake bites. The varying ecological zones of Belize boast over fifty species of snakes, nine of which are poisonous and dangerous to humans. Two distinct Maya groups occupy neighboring regions of Belize, the Q’eqchi’ and the Mopan. With Western medical care often far from their villages, what traditional methods are used to treat poisonous snake bites? Based primarily on data gathered with native consultants during the authors’ fieldwork with both groups, this paper details the ethnobotanical resources used by the Q’eqchi’ and Mopan traditional healers. The Q’eqchi’ and Mopan most commonly rely on traditional ‘bush doctors’ (ilmaj in Mopan), both male and female, and specialized ‘snake doctors’ to heal bites from venomous snakes. First, this paper presents each plant employed by healers for bites for the nine poisonous snakes in Belize along with the specific botanical recipes and methods of application for each remedy. Individual chemical and therapeutic qualities of some of those plants are investigated in an effort to explain their possible medicinal value for different toxins or the symptoms caused by those toxins. In addition, this paper explores mythological associations with certain snakes that inform local understanding regarding which plants are considered efficacious in each case, arguing that numerous oral traditions (recorded by the authors) help to link botanical medicines to episodes within their mythic traditions. Finally, the use of plants to counteract snakebites brought about through sorcery is discussed inasmuch as some snakes are seen as ‘helpers’ of sorcerers. Snake bites given under these circumstances can only be cured by those who know both the proper corresponding plant(s) and ritual prayer(s). This paper provides detailed documentation of traditional ethnomedicines and practices from the dying art of traditional Maya healers and argues for multi-faceted diagnostic techniques to determine toxin severity, the presence or absence of sorcery, and the appropriate botanical remedy.

Keywords: ethnobotany, Maya, medicine, snake bites

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Authors: A. Falenski, A. Kaesbohrer, M. Filter

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Introduction: Risk assessments can be performed in various ways and in different degrees of complexity. In order to assess risks associated with imported foods additional information needs to be taken into account compared to a risk assessment on regional products. The present review is an overview on currently available best practise approaches and data sources used for food import risk assessments (IRAs). Methods: A literature review has been performed. PubMed was searched for articles about food IRAs published in the years 2004 to 2014 (English and German texts only, search string “(English [la] OR German [la]) (2004:2014 [dp]) import [ti] risk”). Titles and abstracts were screened for import risks in the context of IRAs. The finally selected publications were analysed according to a predefined questionnaire extracting the following information: risk assessment guidelines followed, modelling methods used, data and software applied, existence of an analysis of uncertainty and variability. IRAs cited in these publications were also included in the analysis. Results: The PubMed search resulted in 49 publications, 17 of which contained information about import risks and risk assessments. Within these 19 cross references were identified to be of interest for the present study. These included original articles, reviews and guidelines. At least one of the guidelines of the World Organisation for Animal Health (OIE) and the Codex Alimentarius Commission were referenced in any of the IRAs, either for import of animals or for imports concerning foods, respectively. Interestingly, also a combination of both was used to assess the risk associated with the import of live animals serving as the source of food. Methods ranged from full quantitative IRAs using probabilistic models and dose-response models to qualitative IRA in which decision trees or severity tables were set up using parameter estimations based on expert opinions. Calculations were done using @Risk, R or Excel. Most heterogeneous was the type of data used, ranging from general information on imported goods (food, live animals) to pathogen prevalence in the country of origin. These data were either publicly available in databases or lists (e.g., OIE WAHID and Handystatus II, FAOSTAT, Eurostat, TRACES), accessible on a national level (e.g., herd information) or only open to a small group of people (flight passenger import data at national airport customs office). In the IRAs, an uncertainty analysis has been mentioned in some cases, but calculations have been performed only in a few cases. Conclusion: The current state-of-the-art in the assessment of risks of imported foods is characterized by a great heterogeneity in relation to general methodology and data used. Often information is gathered on a case-by-case basis and reformatted by hand in order to perform the IRA. This analysis therefore illustrates the need for a flexible, modular framework supporting the connection of existing data sources with data analysis and modelling tools. Such an infrastructure could pave the way to IRA workflows applicable ad-hoc, e.g. in case of a crisis situation.

Keywords: import risk assessment, review, tools, food import

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Authors: S. M. Chabane sari S. Zargou, A.R. Senoudi, F. Benmouna

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Immobilization of nano particles (NPs) is the subject of numerous studies pertaining to the design of polymer nano composites, supported catalysts, bioactive colloidal crystals, inverse opals for novel optical materials, latex templated-hollow inorganic capsules, immunodiagnostic assays; “Pickering” emulsion polymerization for making latex particles and film-forming composites or Janus particles; chemo- and biosensors, tunable plasmonic nano structures, hybrid porous monoliths for separation science and technology, biocidal polymer/metal nano particle composite coatings, and so on. Particularly, in the recent years, the literature has witnessed an impressive progress of investigations on polymer coatings, grafts and particles as supports for anchoring nano particles. This is actually due to several factors: polymer chains are flexible and may contain a variety of functional groups that are able to efficiently immobilize nano particles and their precursors by dispersive or van der Waals, electrostatic, hydrogen or covalent bonds. We review methods to prepare polymer-immobilized nano particles through a plethora of strategies in view of developing systems for separation, sensing, extraction and catalysis. The emphasis is on methods to provide (i) polymer brushes and grafts; (ii) monoliths and porous polymer systems; (iii) natural polymers and (iv) conjugated polymers as platforms for anchoring nano particles. The latter range from soft bio macromolecular species (proteins, DNA) to metallic, C60, semiconductor and oxide nano particles; they can be attached through electrostatic interactions or covalent bonding. It is very clear that physicochemical properties of polymers (e.g. sensing and separation) are enhanced by anchored nano particles, while polymers provide excellent platforms for dispersing nano particles for e.g. high catalytic performances. We thus anticipate that the synergetic role of polymeric supports and anchored particles will increasingly be exploited in view of designing unique hybrid systems with unprecedented properties.

Keywords: gold, layer, polymer, macromolecular

Procedia PDF Downloads 395

Authors: Kawsar Ahmed, Hong Wang

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The study's goal was to estimate the causal mediation impact of tobacco tax before and after price hikes among low-income male smokers, with a particular emphasis on the effect estimating pathways framework for continuous and dichotomous variables. From July to December 2021, a cross-sectional investigation of observational data (n=739) was collected from Bangladeshi low-wage smokers. The Quasi-Bayesian technique, binomial probit model, and sensitivity analysis using a simulation of the computational tools R mediation package had been used to estimate the effect. After a price rise for tobacco products, the average number of cigarettes or bidis sticks taken decreased from 6.7 to 4.56. Tobacco product rising prices have a direct effect on low-income people's decisions to quit or lessen their daily smoking habits of Average Causal Mediation Effect (ACME) [effect=2.31, 95 % confidence interval (C.I.) = (4.71-0.00), p<0.01], Average Direct Effect (ADE) [effect=8.6, 95 percent (C.I.) = (6.8-0.11), p<0.001], and overall significant effects (p<0.001). Tobacco smoking choice is described by the mediated proportion of income effect, which is 26.1% less of following price rise. The curve of ACME and ADE is based on observational figures of the coefficients of determination that asses the model of hypothesis as the substantial consequence after price rises in the sensitivity analysis. To reduce smoking product behaviors, price increases through taxation have a positive causal mediation with income that affects the decision to limit tobacco use and promote low-income men's healthcare policy.

Keywords: causal mediation analysis, directed acyclic graphs, tobacco price policy, sensitivity analysis, pathway estimation

Procedia PDF Downloads 117

Authors: Yaara Oppenheimer-Shaanan, Nimrod Nachmias, Marina Campos Rocha, Neta Schlezinger, Noam Dotan, Asaf Levy

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Fusarium oxysporum, a fungus that attacks a broad range of plants and can cause infections in humans, operates across different kingdoms. This pathogen encounters varied conditions, such as temperature, pH, and nutrient availability, in plant and human hosts. The Fusarium oxysporum species complex, pervasive in soils globally, can affect numerous plants, including key crops like tomatoes and bananas. Controlling Fusarium infections can involve biocontrol agents that hinder the growth of harmful strains. Our research developed a computational method to identify toxin domains within a vast number of microbial genomes, leading to the discovery of nine distinct toxins capable of killing bacteria and fungi, including Fusarium. These toxins appear to function as enzymes, causing significant damage to cellular structures, membranes and DNA. We explored biological control using bacteria that produce polymorphic toxins, finding that certain bacteria, non-pathogenic to plants, offer a safe biological alternative for Fusarium management, as they did not harm macrophage cells or C. elegans. Additionally, we elucidated the 3D structures of two toxins with their protective immunity proteins, revealing their function as unique DNases. These potent toxins are likely instrumental in microbial competition within plant ecosystems and could serve as biocontrol agents to mitigate Fusarium wilt and related diseases.

Keywords: microbial toxins, antifungal, Fusarium oxysporum, bacterial-fungal intreactions

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Authors: Raluca Ana Maria Viziteu, Anna Prudnikova

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Industrial control systems (ICS) have received much attention in recent years due to the convergence of information technology (IT) and operational technology (OT) that has increased the interdependence of safety and security issues to be considered. These issues require ICS-tailored solutions. That led to the need to creation of a methodology for supporting ICS device manufacturers and system integrators in carrying out threat modeling of embedded ICS devices in a way that guarantees the quality of the identified threats and minimizes subjectivity in the threat identification process. To research, the possibility of creating such a methodology, a set of existing standards, regulations, papers, and publications related to threat modeling in the ICS sector and other sectors was reviewed to identify various existing methodologies and methods used in threat modeling. Furthermore, the most popular ones were tested in an exploratory phase on a specific PLC device. The outcome of this exploratory phase has been used as a basis for defining specific characteristics of ICS embedded devices and their deployment scenarios, identifying the factors that introduce subjectivity in the threat modeling process of such devices, and defining metrics for evaluating the minimum quality requirements of identified threats associated to the deployment of the devices in existing infrastructures. Furthermore, the threat modeling methodology was created based on the previous steps' results. The usability of the methodology was evaluated through a set of standardized threat modeling requirements and a standardized comparison method for threat modeling methodologies. The outcomes of these verification methods confirm that the methodology is effective. The full paper includes the outcome of research on different threat modeling methodologies that can be used in OT, their comparison, and the results of implementing each of them in practice on a PLC device. This research is further used to build a threat modeling methodology tailored to OT environments; a detailed description is included. Moreover, the paper includes results of the evaluation of created methodology based on a set of parameters specifically created to rate threat modeling methodologies.

Keywords: device manufacturers, embedded devices, industrial control systems, threat modeling

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Authors: Khairil Iskandar Othman, Nadhirah Kamal, Zarina Bibi Ibrahim

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Block methods for solving stiff systems of ordinary differential equations (ODEs) are based on backward differential formulas (BDF) with PE(CE)2 and Newton method. In this paper, we introduce Modified Newton as a new strategy to get more efficient result. The derivation of BBDF using modified block Newton method is presented. This new block method with predictor-corrector gives more accurate result when compared to the existing BBDF.

Keywords: modified Newton, stiff, BBDF, Jacobian matrix

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Authors: Jian Li

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The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

Procedia PDF Downloads 89

Authors: Hannah M. Russell

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‘The Attach Project’ (TAP), is an educational intervention aimed at improving educational and socio-emotional outcomes for children who are looked after. TAP is underpinned by Attachment Theory and is adapted from Dyadic Developmental Psychotherapy (DDP), which is a treatment for children and young people impacted by complex trauma and disorders of attachment. TAP has been implemented in primary schools in Northern Ireland throughout the 2018/19 academic year. During this time, a design and implementation study has been conducted to assess the promise of effectiveness for the future dissemination and ‘scaling-up’ of the programme for a larger, randomised control trial. TAP has been designed specifically for implementation in a school setting and is comprised of a whole school element and a more individualised Key Adult-Key Child pairing. This design and implementation study utilises a mixed-methods research design consisting of quantitative, qualitative, and observational measures with stakeholder input and involvement being considered an integral component. The use of quantitative measures, such as self-report questionnaires prior to and eight months following the implementation of TAP, enabled the analysis of the strengths and direction of relations between the various components of the programme, as well as the influence of implementation factors. The use of qualitative measures, incorporating semi-structured interviews and focus groups, enabled the assessment of implementation factors, identification of implementation barriers, and potential methods of addressing these issues. Observational measures facilitated the continual development and improvement of ‘TAP training’ for school staff. Preliminary findings have provided evidence of promise for the effectiveness of TAP and indicate the potential benefits of introducing this type of attachment-based intervention across other educational settings. This type of intervention could benefit not only children who are looked after but all children who may be impacted by complex trauma or disorders of attachment. Furthermore, findings from this study demonstrate that it is possible for children to form a secondary attachment relationship with a significant adult in school. However, various implementation factors which should be addressed were identified throughout the study, such as the necessity of protected time being introduced to facilitate the development of a positive Key Adult- Key Child relationship. Furthermore, additional ‘re-cap’ training is required in future dissemination of the programme, to maximise ‘attachment friendly practice’ in the whole staff team. Qualitative findings have also indicated that there is a general opinion across school staff that this type of Key Adult- Key Child pairing could be more effective if it was introduced as soon as children begin primary school. This research has provided ample evidence for the need to introduce relationally based interventions in schools, to help to ensure that children who are looked after, or who are impacted by complex trauma or disorders of attachment, can thrive in the school environment. In addition, this research has facilitated the identification of important implementation factors and barriers to implementation, which can be addressed prior to the ‘scaling-up’ of TAP for a robust, randomised controlled trial.

Keywords: attachment, complex trauma, educational interventions, implementation

Procedia PDF Downloads 200