Search results for: hub domain

Authors: Ali Akbar, Seungho Shin, Sukkee Um

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The composition of catalyst layers (CLs) plays an important role in the overall performance and cost of the proton exchange membrane fuel cells (PEMFCs). Low platinum loading, high utilization, and more durable catalyst still remain as critical challenges for PEMFCs. In this study, a three-dimensional material network model is developed to visualize the nanostructure of carbon supported platinum Pt/C and Pt/VACNT catalysts in pursuance of maximizing the catalyst utilization. The quadruple-phase randomly generated CLs domain is formulated using quasi-random stochastic Monte Carlo-based method. This unique statistical approach of four-phase (i.e., pore, ionomer, carbon, and platinum) model is closely mimic of manufacturing process of CLs. Various CLs compositions are simulated to elucidate the effect of electrons, ions, and mass transport paths on the catalyst utilization factor. Based on simulation results, the effect of key factors such as porosity, ionomer contents and Pt weight percentage in Pt/C catalyst have been investigated at the represented elementary volume (REV) scale. The results show that the relationship between ionomer content and Pt utilization is in good agreement with existing experimental calculations. Furthermore, this model is implemented on the state-of-the-art Pt/VACNT CLs. The simulation results on Pt/VACNT based CLs show exceptionally high catalyst utilization as compared to Pt/C with different composition ratios. More importantly, this study reveals that the maximum catalyst utilization depends on the distance spacing between the carbon nanotubes for Pt/VACNT. The current simulation results are expected to be utilized in the optimization of nano-structural construction and composition of Pt/C and Pt/VACNT CLs.

Keywords: catalyst layer, platinum utilization, proton exchange membrane fuel cell, stochastic modeling

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Sanjal Gavande, Thomas Mazzuchi, Shahram Sarkani

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In a complex aerospace operational environment, identifying failures in a procedure involving multiple human-machine interactions are difficult. These failures could lead to accidents causing loss of hardware or human life. The likelihood of failure further increases if operational procedures are tested for a novel system with multiple human-machine interfaces and with no prior performance data. The existing approach in the literature of reviewing complex operational tasks in a flowchart or tabular form doesn’t provide any insight into potential system failures due to human decision-making ability. To address these challenges, this research explores an agent-based simulation approach for reliability assessment and fault detection in complex human-machine systems while utilizing a human decision-making model. The simulation will predict the emergent behavior of the system due to the interaction between humans and their decision-making capability with the varying states of the machine and vice-versa. Overall system reliability will be evaluated based on a defined set of success-criteria conditions and the number of recorded failures over an assigned limit of Monte Carlo runs. The study also aims at identifying high-likelihood failure locations for the system. The research concludes that system reliability and failures can be effectively calculated when individual human and machine agent states are clearly defined. This research is limited to the operations phase of a system lifecycle process in an aerospace environment only. Further exploration of the proposed agent-based and human decision-making model will be required to allow for a greater understanding of this topic for application outside of the operations domain.

Keywords: agent-based model, complex human-machine system, human decision-making model, system reliability assessment

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Authors: Phanindra Prasad Thummala, Umran Tezcan Un, Ahmet Ozan Celik

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Removal of CO₂ by MEA (monoethanolamine) in structured packing columns depends highly on the gas-liquid interfacial area and film thickness (liquid load). CFD (computational fluid dynamics) is used to find the interfacial area, film thickness and their impact on mass transfer in gas-liquid flow effectively in any column geometry. In general modeling approaches used in CFD derive mass transfer parameters from standard correlations based on penetration or surface renewal theories. In order to avoid the effect of assumptions involved in deriving the correlations and model the mass transfer based solely on fluid properties, state of art approaches like one fluid formulation is useful. In this work, the one fluid formulation was implemented and evaluated for modeling the physical mass transfer of CO₂ by N₂O analogy in OpenFOAM CFD software. N₂O analogy avoids the effect of chemical reactions on absorption and allows studying the amount of CO₂ physical mass transfer possible in a given geometry. The computational domain in the current study was a flat plate with gas and liquid flowing in the countercurrent direction. The effect of operating parameters such as flow rate, the concentration of MEA and angle of inclination on the physical mass transfer is studied in detail. Liquid side mass transfer coefficients obtained by simulations are compared to the correlations available in the literature and it was found that the one fluid formulation was effectively capturing the effects of interface surface instabilities on mass transfer coefficient with higher accuracy. The high mesh refinement near the interface region was found as a limiting reason for utilizing this approach on large-scale simulations. Overall, the one fluid formulation is found more promising for CFD studies involving the CO₂ mass transfer.

Keywords: one fluid formulation, CO₂ absorption, liquid mass transfer coefficient, OpenFOAM, N₂O analogy

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Authors: Jiří Vágner, Dana Fialová

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The Covid-19 pandemic and its effects have triggered significant changes in travel behavior. On the contrary to a deep decline in international tourism, domestic tourism has recovered. It has not fully replaced the total volume of national tourism so far. However, from a regional point of view, and especially according to the type of destinations, regional targeting has changed significantly compared to the previous period. Urban destinations, which used to be the domain of foreign tourists, have been relatively orphaned, in contrast to destinations tied to natural attractions, which have seen seasonal increases. Even here, at a lower hierarchical geographic level, we can observe the differentiation resulting from the existing localization and infrastructure. The case study is focused on the three largest water reservoirs of the Vltava Cascade in Czechia– Lipno, Orlík, and Slapy. Based on a detailed field survey, in the periods before and during the pandemic, as well as available statistical data (Tourdata; Czech Statistical Office, Czech Cadaster and Ordnance Survey), different trends in the exploitation of these destinations with regard to existing or planned infrastructure are documented, analyzed and explained. This gives us the opportunity to discuss on concrete examples of generally known phenomena that are usually neglected in tourism: slum, brownfield, greenfield. Changes in travel behavior – especially the focus on spending leisure time individually in naturally attractive destinations – can affect the use of sites, which can be defined as a tourist or recreational slum, brownfield, but also as a tourist greenfield development. Sociocultural changes and perception of destinations by tourists and other actors represent, besides environmental changes, major trends in current tourism.

Keywords: Covid-19 pandemic, czechia, sociocultural and environmental impacts, tourist infrastructure, travel behavior, the Vltava Cascade water reservoirs

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Authors: Milagros S. Salibad, Levita B. Grana

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The presence and role of Indigenous Peoples (IPs) residing in key biodiversity, protected, and watershed areas within the ancestral domain in the Caraga region, Mindanao, Philippines, hold immense significance. Recognizing their importance and rights, this study aimed to determine the level of biodiversity conservation practices and extent of environmental stewardship among the Mamanwas, Manobos, and Higaonons, assess potential differences in these practices, and identify factors that facilitate or hinder them. Employing an explanatory sequential mixed-method research design, 421 respondents participated through a researcher-made questionnaire. Additional data were collected through focus group discussions, key informant interviews, researcher field notes, community immersions, and secondary sources. The results revealed a high level of biodiversity conservation practices across the three IP groups, with variations influenced by their cultural and traditional practices, awareness, and access to resources and information. Each group exhibited unique environmental practices shaped by their distinct cultures, traditions, and customary knowledge. They have a strong sense of ownership and responsibility towards their ancestral lands and territories and adopt traditional knowledge and practices that promote sustainable resource management and biodiversity conservation. These practices align with the Indigenous Peoples Rights Act (IPRA), also known as Republic Act No. 8371. Various facilitating and hindering factors influenced their conservation efforts. To uphold the region's biodiversity resources, it is recommended that government agencies continue to evaluate and monitor the sustainability of IPs' local biodiversity conservation practices. Additionally, efforts should be made to involve IP communities as essential contributors and stakeholders in these conservation endeavors.

Keywords: biodiversity, conservation, indigenous peoples, traditional knowledge, environmental stewardship

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Authors: Michael Luc Andre, Célia Maintenant

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Theory of mind is a milestone in child development which allows children to understand that others could have different mental states than theirs. Understanding the developmental stages of theory of mind in children leaded researchers on two Connected research problems. In one hand, the link between executive function and theory of mind, and on the other hand, the relationship of theory of mind and syntax processing. These two lines of research involved a great literature, full of important results, despite certain level of disagreement between researchers. For a long time, these two research perspectives continue to grow up separately despite research conclusion suggesting that the three variables should implicate same developmental period. Indeed, our goal was to study the relation between theory of mind, executive function, and language via a unique research question. It supposed that between executive function and language, one of the two variables could play a critical role in the relationship between theory of mind and the other variable. Thus, 112 children aged between three and six years old were recruited for completing a receptive and an expressive vocabulary task, a syntax understanding task, a theory of mind task, and three executive function tasks (inhibition, cognitive flexibility and working memory). The results showed significant correlations between performance on theory of mind task and performance on executive function domain tasks, except for cognitive flexibility task. We also found significant correlations between success on theory of mind task and performance in all language tasks. Multiple regression analysis justified only syntax and general abilities of language as possible predictors of theory of mind performance in our preschool age children sample. The results were discussed in the perspective of a great role of language abilities in theory of mind development. We also discussed possible reasons that could explain the non-significance of executive domains in predicting theory of mind performance, and the meaning of our results for the literature.

Keywords: child development, executive function, general language, syntax, theory of mind

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Authors: Jayotpaul Chaudhuri, Lutz Goedeke, Torsten Hallenga, Peter Ehrhard

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Purification of gases from aerosols or airborne particles via filters is widely applied in the industry and in our daily lives. This separation especially in the micron and submicron size range is a necessary step to protect the environment and human health. Fibrous filters are often employed due to their low cost and high efficiency. For designing any filter the two most important performance parameters are capture efficiency and pressure drop. Since the capture efficiency is directly proportional to the pressure drop which leads to higher operating costs, a detailed investigation of the separation mechanism is required to optimize the filter designing, i.e., to have a high capture efficiency with a lower pressure drop. Therefore a two-dimensional flow simulation around a single fiber using Ansys CFX and Matlab is used to get insight into the separation process. Instead of simulating a solid fiber, the present Ansys CFX model uses a fictitious domain approach for the fiber by implementing a momentum loss model. This approach has been chosen to avoid creating a new mesh for different fiber sizes, thereby saving time and effort for re-meshing. In a first step, only the flow of the continuous fluid around the fiber is simulated in Ansys CFX and the flow field data is extracted and imported into Matlab and the particle trajectory is calculated in a Matlab routine. This calculation is a Lagrangian, one way coupled approach for particles with all relevant forces acting on it. The key parameters for the simulation in both Ansys CFX and Matlab are the porosity ε, the diameter ratio of particle and fiber D, the fluid Reynolds number Re, the Reynolds particle number Rep, the Stokes number St, the Froude number Fr and the density ratio of fluid and particle ρf/ρp. The simulation results were then compared to the single fiber theory from the literature.

Keywords: BBO-equation, capture efficiency, CFX, Matlab, fibrous filter, particle trajectory

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Authors: Lokanath Barik, Abinash Kumar Swain

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This paper presents vibration analysis of FGM sandwich structure with a complex profile governed by refined higher-order shear deformation theory (RHSDT) using isogeometric analysis (IGA). Functionally graded sandwich plates provide a wide range of applications in aerospace, defence, and aircraft industries due to their ability to distribute material functions to influence the thermo-mechanical properties as desired. In practical applications, these structures generally have intrinsic profiles, and their response to loads is significantly affected due to cut-outs. IGA is primarily a NURBS-based technique that is effective in solving higher-order differential equations due to its inherent C1 continuity imposition in solution space for a single patch. Complex structures generally require multiple patches to accurately represent the geometry, and hence, there is a loss of continuity at adjoining patch junctions. Therefore, patch coupling is desired to maintain continuity requirements throughout the domain. In this work, a novel strong coupling approach is provided that generates a well-defined NURBS-based model while achieving continuity. The methodology is validated by free vibration analysis of sandwich plates with present literature. The results are in good agreement with the analytical solution for different plate configurations and power law indexes. Numerical examples of rectangular and annular plates are discussed with variable boundary conditions. Additionally, parametric studies are provided by varying the aspect ratio, porosity ratio and their influence on the natural frequency of the plate.

Keywords: vibration analysis, FGM sandwich structure, multipatch geometry, patch coupling, IGA

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Authors: Himanshu Singh, Rishi Kant, Shantanu Bhattacharya

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This paper adopts a top-down approach for mathematical modeling to predict the size reduction from micro to nano-scale through persistent etching. The process is simulated using a finite difference approach. Previously, various researchers have simulated the etching process for 1-D and 2-D substrates. It consists of two processes: 1) Convection-Diffusion in the etchant domain; 2) Chemical reaction at the surface of the particle. Since the process requires analysis along moving boundary, partial differential equations involved cannot be solved using conventional methods. In 1-D, this problem is very similar to Stefan's problem of moving ice-water boundary. A fixed grid method using finite volume method is very popular for modelling of etching on a one and two dimensional substrate. Other popular approaches include moving grid method and level set method. In this method, finite difference method was used to discretize the spherical diffusion equation. Due to symmetrical distribution of etchant, the angular terms in the equation can be neglected. Concentration is assumed to be constant at the outer boundary. At the particle boundary, the concentration of the etchant is assumed to be zero since the rate of reaction is much faster than rate of diffusion. The rate of reaction is proportional to the velocity of the moving boundary of the particle. Modelling of the above reaction was carried out using Matlab. The initial particle size was taken to be 50 microns. The density, molecular weight and diffusion coefficient of the substrate were taken as 2.1 gm/cm3, 60 and 10-5 cm2/s respectively. The etch-rate was found to decline initially and it gradually became constant at 0.02µ/s (1.2µ/min). The concentration profile was plotted along with space at different time intervals. Initially, a sudden drop is observed at the particle boundary due to high-etch rate. This change becomes more gradual with time due to declination of etch rate.

Keywords: particle size reduction, micromixer, FDM modelling, wet etching

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Authors: P. Mukhopadhyay, N. C. Dey

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Occupational health hazard is a very common term in every emerging country. Along with the unorganized sector, most organized sectors including government industries are suffering from this affliction. In addition to workload, the seasonal changes also have some impacts on working environment. With this focus in mind, one hundred male industrial workers, who are directly involved to the task of Periodic Overhauling (POH) in a fabricating workshop in the public domain are selected for this research work. They have been studied during work periods throughout different seasons in a year. For each and every season, the participants working heart rate (WHR) is measured and compared with the standards given by different national and internationally recognized agencies i.e., World Health Organization (WHO) and American Conference of Governmental Industrial Hygienists (ACGIH) etc. The different environmental parameters i.e. dry bulb temperature (DBT), wet bulb temperature (WBT), globe temperature (GT), natural wet bulb temperature (NWB), relative humidity (RH), wet bulb globe temperature (WBGT), air velocity (AV), effective temperature (ET) are recorded throughout the seasons to critically observe the effect of seasonal changes on the WHR of the workers. The effect of changes in environment to the WHR of the workers is very much surprising. It is found that the percentages of workers who belong to the ‘very heavy’ workload category are 83.33%, 66.66% and 16.66% in the summer, rainy and winter seasons, respectively. Ongoing undertaking of this type of job profile forces the worker towards occupational disorders causing absenteeism. This occurrence results in lower production rates, and on the other hand, costs due to medical claims also weaken the industry’s economic condition. In this circumstance, the authors are trying to focus on some remedial measures from the ergonomic angle by proposing a new work/ rest regimen and introducing engineering controls along with management controls which may help the worker, and consequently, the management also.

Keywords: workload, working heart rate, occupational health hazard, industrial worker

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Authors: Amir Sattari, Mac Panah, Naeim Rashidfarokhi

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To enhance the mixing of fluid in a rectangular enclosure with a circular inlet and outlet, an energy-efficient approach is further investigated through computational fluid dynamics (CFD). Particle image velocimetry (PIV) measurements help confirm that the pulsation of the inflow velocity improves the mixing performance inside the enclosure considerably without increasing energy consumption. In this study, multiple CFD simulations with different turbulent models were performed. The results obtained were compared with experimental PIV results. This study investigates small-scale representations of flow patterns in a ventilated rectangular room. The objective is to validate the concept of an energy-efficient ventilation strategy with improved thermal comfort and reduction of stagnant air inside the room. Experimental and simulated results confirm that through pulsation of the inflow velocity, strong secondary vortices are generated downstream of the entrance wall-jet. The pulsatile inflow profile promotes a periodic generation of vortices with stronger eddies despite a relatively low inlet velocity, which leads to a larger boundary layer with increased kinetic energy in the occupied zone. A real-scale study was not conducted; however, it can be concluded that a constant velocity inflow profile can be replaced with a lower pulsated flow rate profile while preserving the mixing efficiency. Among the turbulent CFD models demonstrated in this study, SST-kω is most advantageous, exhibiting a similar global airflow pattern as in the experiments. The detailed near-wall velocity profile is utilized to identify the wall-jet instabilities that consist of mixing and boundary layers. The SAS method was later applied to predict the turbulent parameters in the center of the domain. In both cases, the predictions are in good agreement with the measured results.

Keywords: CFD, PIV, pulsatile inflow, ventilation, wall-jet

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Authors: Abdorrasoul Malekpour, Mohammad Ghorbani Mojtaba Mortazavi, Mohammadreza Fattahi, Mohammad Hassan Meshkibaf, Ali Fakhrzad, Saeid Salehi, Saeideh Zahedi, Amir Ahmadimoghaddam, Parviz Farzadnia Dr., Mohammadreza Hajyani Asl Bs

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Hepatitis B as an infectious disease has eight main genotypes (A–H). The aim of this study is to Bioinformatically identify Rare Codon Clusters (RCC) in proteins structure of HBV. For detection of protein family accession numbers (Pfam) of HBV proteins; used of uni-prot database and Pfam search tool were used. Obtained Pfam IDs were analyzed in Sherlocc program and RCCs in HBV proteins were detected. In further, the structures of TrEMBL entries proteins studied in PDB database and 3D structures of the HBV proteins and locations of RCCs were visualized and studied using Swiss PDB Viewer software. Pfam search tool have found nine significant hits and 0 insignificant hits in 3 frames. Results of Pfams studied in the Sherlocc program show this program not identified RCCs in the external core antigen (PF08290) and truncated HBeAg protein (PF08290). By contrast the RCCs become identified in Hepatitis core antigen (PF00906) Large envelope protein S (PF00695), X protein (PF00739), DNA polymerase (viral) N-terminal domain (PF00242) and Protein P (Pf00336). In HBV genome, seven RCC identified that found in hepatitis core antigen, large envelope protein S and DNA polymerase proteins and proteins structures of TrEMBL entries sequences that reported in Sherlocc program outputs are not complete. Based on situation of RCC in structure of HBV proteins, it suggested those RCCs are important in HBV life cycle. We hoped that this study provide a new and deep perspective in protein research and drug design for treatment of HBV.

Keywords: rare codon clusters, hepatitis B virus, bioinformatic study, infectious disease

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Authors: Ishan Tank, Ashmita Rupal, Sanjay Kumar Sharma

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Concrete, a widely used building material, has cement as its main constituent. An excessive amount of emissions are released into the atmosphere during the manufacture of cement, which is detrimental to the environment. To minimize this problem, innovative materials like geopolymer mortar (GPM) seem to be a better alternative. By using fly ash-based geopolymer instead of standard cement mortar as a binding ingredient, this concept has been successfully applied to the building sector. The advancement of this technology significantly reduces greenhouse gas emissions and helps in source reduction, thereby minimizing pollution of the environment. In order to produce mortar and use this geopolymer mortar in the development of building materials, the current investigation is properly introducing this geopolymeric material, namely fly ash, as a binder in place of standard cement. In the domain of the building material industry, fly ash based geopolymer is a new and optimistic replacement for traditional binding materials because it is both environmentally sustainable and has good durability. The setting behaviour and strength characteristics of fly ash, when mixed with alkaline activator solution with varied concentration of sodium hydroxide solution, alkaline liquids mix ratio, and curing temperature, must be investigated, though, in order to determine its suitability and application in comparison with the traditional binding material, by activating the raw materials, which include various elements of silica and alumina, finer material known as geopolymer mortar is created. The concentration of the activator solution has an impact on the compressive strength of the geopolymer concrete formed. An experimental examination of compressive strength after 7, 14, and 28 days of fly ash-based geopolymer concrete is presented in this paper. Furthermore, the process of geopolymerization largely relies on the curing temperature. So, the setting time of Geopolymer mortar due to different curing temperatures has been studied and discussed in this paper.

Keywords: geopolymer mortar, setting time, flyash, compressive strength, binder material

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Authors: Gholamreza Hashemitabr, Reza Valadan, Alireza Rafiei, Mohammad Reza Bassami

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Breast cancer is the most common malignancy among women worldwide. Cancer cells use a complex multilayer network of epidermal growth factor receptors (EGFRs) signaling pathways to support their survival and growth. The overlapping networks of EGFRs signaling pathways account for the failure of most ErbB-targeted therapies. The aim of this study was to enrich a pool of recombinant antibody fragments against common epitopes of ErbB1 and ErbB2 in order to simultaneous blockade of ErbBs signaling pathways. ErbB1 and ErbB2 were expressed stably in VERO cells. Selection of recombinant antibodies was performed on live cells expressing either of ErbB1 and ErbB2 receptors using subtractive phage display approach. The results of PCR and DNA fingerprinting in the last round of panning showed that most clones contained insert (80% and 85% for ErbB1 and ErbB2 respectively) with an identical restriction pattern. The selected clones showed positive reaction to both ErbB1 and ErbB2 receptors in phage-ELISA test. Furthermore, the resulting soluble antibody fragments recognized common epitopes of both immunoprecipitated ErbB1 and ErbB2 in western blot. Additionally, the antibodies directed against the dimerization domain of ErbB1 demonstrated a significant absorbance in EGF-stimulated VERO/ErbB1 cells than non-stimulated cells (1.91 and 1.09 respectively). Moreover, the results of dimerization inhibition test showed that these antibodies blocked ErbB1 and ErbB2 dimerization on the surface of ErbB1 and ErbB2 expressing VERO cells. Regarding the importance of pan-ErbB approach to cancer therapy, the antibodies developed here might provide novel therapeutics for simultaneous blockade of ErbBs signaling pathways.

Keywords: breast cancer, single-chain antibody, ErbB1, ErbB2, epitope

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Authors: Miriam Sosa-Díaz, Faustino Sánchez-Garduño

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In population dynamics the study of both, the abundance and the spatial distribution of the populations in a given habitat, is a fundamental issue a From ecological point of view, the determination of the factors influencing such changes involves important problems. In this paper a mathematical model to describe the temporal dynamic and the spatiotemporal dynamic of the interaction of three populations (pollinators, plants and herbivores) is presented. The study we present is carried out by stages: 1. The temporal dynamics and 2. The spatio-temporal dynamics. In turn, each of these stages is developed by considering three cases which correspond to the dynamics of each type of interaction. For instance, for stage 1, we consider three ODE nonlinear systems describing the pollinator-plant, plant-herbivore and plant-pollinator-herbivore, interactions, respectively. In each of these systems different types of dynamical behaviors are reported. Namely, transcritical and pitchfork bifurcations, existence of a limit cycle, existence of a heteroclinic orbit, etc. For the spatiotemporal dynamics of the two mathematical models a novel factor are introduced. This consists in considering that both, the pollinators and the herbivores, move towards those places of the habitat where the plant population density is high. In mathematical terms, this means that the diffusive part of the pollinators and herbivores equations depend on the plant population density. The analysis of this part is presented by considering pairs of populations, i. e., the pollinator-plant and plant-herbivore interactions and at the end the two mathematical model is presented, these models consist of two coupled nonlinear partial differential equations of reaction-diffusion type. These are defined on a rectangular domain with the homogeneous Neumann boundary conditions. We focused in the role played by the density dependent diffusion term into the coexistence of the populations. For both, the temporal and spatio-temporal dynamics, a several of numerical simulations are included.

Keywords: bifurcation, heteroclinic orbits, steady state, traveling wave

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Authors: Sina Mahdavi, Mahdi Asghari Ozma

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Multiple sclerosis (MS) is the most common inflammatory autoimmune disease of the CNS that affects the myelination process in the central nervous system (CNS). Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially human Varicella-zoster virus (VZV) and MS is one potential cause that is not well understood. This study aims to summarize the available data on VZV retrovirus infection in MS disease progression. For this study, the keywords "Multiple sclerosis", " Human Varicella-zoster virus ", and "central nervous system" in the databases PubMed, Google Scholar, Sid, and MagIran between 2016 and 2022 were searched and 14 articles were chosen, studied, and analyzed. Analysis of the amino acid sequences of HNRNPA1 with VZV proteins has shown a 62% amino acid sequence similarity between VZV gE and the PrLD/M9 epitope region (TNPO1 binding domain) of mutant HNRNPA1. A heterogeneous nuclear ribonucleoprotein (hnRNP), which is produced by HNRNPA1, is involved in the processing and transfer of mRNA and pre-mRNA. Mutant HNRNPA1 mimics gE of VZV as an antigen that leads to autoantibody production. Mutant HnRNPA1 translocates to the cytoplasm, after aggregation is presented by MHC class I, followed by CD8 + cells. Of these, antibodies and immune cells against the gE epitopes of VZV remain due to the memory immune response, causing neurodegeneration and the development of MS in genetically predisposed individuals. VZV expression during the course of MS is present in genetically predisposed individuals with HNRNPA1 mutation, suggesting a link between VZV and MS, and that this virus may play a role in the development of MS by inducing an inflammatory state. Therefore, measures to modulate VZV expression may be effective in reducing inflammatory processes in demyelinated areas of MS patients in genetically predisposed individuals.

Keywords: multiple sclerosis, varicella-zoster virus, central nervous system, autoimmunity

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Authors: Virakti Dhaval Shah

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Advances in technology and the changes in lifestyle and work expectations amid the COVID-19 pandemic are requiring changes to vocational assessment, provision of vocational training, and identification of job matches for individuals with intellectual disability. Vocational assessment involves the assessment of interests, skills, abilities, and strengths/weaknesses, as well as a detailed understanding of healthcare, familial, social, community, workplace-related and policy-level protective and risk factors impacting the individual. In India, vocational assessment procedures such as interviews play a major role in vocational placement today. Unfortunately, many of the most widely used vocational assessment instruments in India were developed in the 1970s to 2000s and have not been revised since. Hence, there is a dire need to update existing tools and prepare a structured approach for vocational service providers to meet the unique employment needs of individuals with intellectual disabilities. To address this need, this project designed a multi-domain assessment toolkit for a structured approach to vocational assessment, training, and job placement for individuals with intellectual disabilities in India. Methods included conducting an empirical review of the available tools currently in use in India for the vocational assessment of persons with intellectual disabilities. Domains addressed in the instrument review were organized into a structured system, and additional items related to contemporary technology, pandemic-related experiences of persons with disabilities, and changes in lifestyle and work expectations due to the pandemic were added. Items assessing behaviors, provision of vocational training, and identification of job matches for individuals with intellectual disabilities were developed. The proposed tool has the potential to benefit organizations working with and preparing individuals with intellectual disabilities to find successful employment by undertaking a structured approach to vocational assessment, rehabilitation, training, and placement. It can be particularly useful for guiding new professionals doing vocational rehabilitation in India.

Keywords: intellectual disability, rehabilitation, vocational assessment, vocational rehabilitation

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Authors: Dheyaa Hussein, Peter Armstrong

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The phenomenon of visual disorder is prominent in contemporary townscapes. This paper provides a theoretical framework for the assessment of visual consistency in townscape in order to achieve more favourable outcomes for users. In this paper, visual consistency refers to the amount of similarity between adjacent components of townscape. The paper investigates parameters which relate to visual consistency in townscape, explores the relationships between them and highlights their significance. The paper uses arithmetic methods from outside the domain of urban design to enable the establishment of an objective approach of assessment which considers subjective indicators including users’ preferences. These methods involve the standard of deviation, colour distance and the distance between points. The paper identifies urban space as a key representative of the visual parameters of townscape. It focuses on its two components, geometry and colour in the evaluation of the visual consistency of townscape. Accordingly, this article proposes four measurements. The first quantifies the number of vertices, which are points in the three-dimensional space that are connected, by lines, to represent the appearance of elements. The second evaluates the visual surroundings of urban space through assessing the location of their vertices. The last two measurements calculate the visual similarity in both vertices and colour in townscape by the calculation of their variation using methods including standard of deviation and colour difference. The proposed quantitative assessment is based on users’ preferences towards these measurements. The paper offers a theoretical basis for a practical tool which can alter the current understanding of architectural form and its application in urban space. This tool is currently under development. The proposed method underpins expert subjective assessment and permits the establishment of a unified framework which adds to creativity by the achievement of a higher level of consistency and satisfaction among the citizens of evolving townscapes.

Keywords: townscape, urban design, visual assessment, visual consistency

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Authors: Robin V. Cupido

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Online dispute resolution has been identified in many countries as a viable alternative for resolving conflicts which have arisen in the so-called digital age. This system of dispute resolution is developing alongside the Internet, and as new types of transactions are made possible by our increased connectivity, new ways of resolving disputes must be explored. Developed nations, such as the United States of America and the European Union, have been involved in creating these online dispute resolution mechanisms from the outset, and currently have sophisticated systems in place to deal with conflicts arising in a number of different fields, such as e-commerce, domain name disputes, labour disputes and conflicts arising from family law. Specifically, in the field of e-commerce, the Internet’s borderless nature has served as a way to promote cross-border trade, and has created a global marketplace. Participation in this marketplace boosts a country’s economy, as new markets are now available, and consumers can transact from anywhere in the world. It would be especially advantageous for developing nations to be a part of this global marketplace, as it could stimulate much-needed investment in these nations, and encourage international co-operation and trade. However, for these types of transactions to proliferate, an effective system for resolving the inevitable disputes arising from such an increase in e-commerce is needed. Online dispute resolution scholarship and practice is flourishing in developed nations, and it is clear that the gap is widening between developed and developing nations in this regard. The potential for implementing online dispute resolution in developing countries has been discussed, but there are a number of obstacles that have thus far prevented its continued development. This paper aims to evaluate the various political, infrastructural and socio-economic challenges faced in developing nations, and to question how these have impacted the acceptance and development of online dispute resolution, scholarship and training of online dispute resolution practitioners and, ultimately, developing nations’ readiness to participate in cross-border e-commerce.

Keywords: developing countries, feasibility, online dispute resolution, progress

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Authors: Mohsen Hasirian, Amir Shahab Shahabi

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Modern societies, marked by expansive Internet connectivity and the rise of e-commerce, are now integrated with digital platforms at an unprecedented level. The efficiency, speed, and accessibility of e-commerce have garnered a substantial consumer base. Against this backdrop, electronic banking has undergone rapid proliferation within the realm of online activities. However, this growth has inadvertently given rise to an environment conducive to illicit activities, notably electronic payment fraud, posing a formidable challenge to the domain of electronic banking. A pivotal role in upholding the integrity of electronic commerce and business transactions is played by electronic fraud detection, particularly in the context of credit cards which underscores the imperative of comprehensive research in this field. To this end, our study introduces an Attentional Bi-Stream Sequence Learner (AttBiSeL) framework that leverages attention mechanisms and recurrent networks. By incorporating bidirectional recurrent layers, specifically bidirectional Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) layers, the proposed model adeptly extracts past and future transaction sequences while accounting for the temporal flow of information in both directions. Moreover, the integration of an attention mechanism accentuates specific transactions to varying degrees, as manifested in the output of the recurrent networks. The effectiveness of the proposed approach in automatic credit card fraud classification is evaluated on the European Cardholders' Fraud Dataset. Empirical results validate that the hybrid architectural paradigm presented in this study yields enhanced accuracy compared to previous studies.

Keywords: credit card fraud, deep learning, attention mechanism, recurrent neural networks

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Authors: Jack Buckhill Khallahle

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In this study, the calculation methods for interfacial and gas wall shear stress in two-phase flow over a stationary liquid surface with dissimilar liquid viscosities within a horizontal pipe are explored. The research focuses on understanding the behavior of gas and liquid phases as they interact in confined pipe geometries, with liquid-water and kerosene serving as the stationary surfaces. To achieve accurate modelling of flow variables such as pressure drop, liquid holdup, and shear stresses in such flow configurations, a 3D pipe model is developed for Computational Fluid Dynamics (CFD) simulation. This model simulates fully developed gas flow over a stationary liquid surface within a 2.2-liter reservoir of 6.25 meters length and 0.05 meters pipe diameter. The pipe geometry is specifically configured based on the experimental setup used by Newton et al [23]. The simulations employ the Volume of Fluid (VOF) model to track the gas-liquid interface in the two-phase domain. Additionally, the k-ω Shear Stress Transport (SST) turbulence model is used to address turbulence effects in the flow field. The governing equations are solved using the Pressure-Implicit with Splitting of Operators (PISO) algorithm. The model is validated by calculating liquid heights, gas wall, and interfacial shear stresses and comparing them against experimental data for both water and kerosene. Notably, the proposed interfacial friction factor correlation based on the employed pipe model aligns excellently with experimental data using the conventional two-phase flow calculation method. However, it is observed that the interfacial and gas wall shear stresses calculated from mathematical formulations involving hydrostatic force exhibit poor correlation with the experimental data.

Keywords: Two-Phase Flow, Horizontal Pipe, VOF Model, k-ω SST Model, Stationary Liquid Surface, Gas Wall and Interfacial Shear Stresses and Hydrostatic Force.

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Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli

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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are playing an increasingly important role in automated customer service. These models, which are able to recognize complex relationships between input and output sequences, are crucial for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the focus of the model during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the domain of chatbots using the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Utilizing the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k=3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k=3). These results emphasize the crucial influence of selecting an appropriate attention-scoring function in improving the performance of seq2seq models for chatbots. Particularly, the model that integrates tanh activation proves to be a promising approach to improve the quality of chatbots in the customer support context.

Keywords: attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence

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Authors: Mark Andrew

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Geopolitical tensions are at a thirty-year high, and the pace of technological innovation is driving asymmetry in force capabilities between nation states and between non-state actors. Technology futures are a vital component of defence capability growth, and investments in technology futures need to be informed by accurate and reliable forecasts of the options for ‘systems of systems’ innovation, development, and deployment. This paper describes a method for forecasting technology futures developed through an analysis of four key systems’ development stages, namely: technology domain categorisation, scanning results examining novel systems’ signals and signs, potential system-of systems’ implications in warfare theatres, and political ramifications in terms of funding and development priorities. The method has been applied to several technology domains, including physical systems (e.g., nano weapons, loitering munitions, inflight charging, and hypersonic missiles), biological systems (e.g., molecular virus weaponry, genetic engineering, brain-computer interfaces, and trans-human augmentation), and information systems (e.g., sensor technologies supporting situation awareness, cyber-driven social attacks, and goal-specification challenges to proliferation and alliance testing). Although the current application of the method has been team-centred using paper-based rapid prototyping and iteration, the application of autonomous language models (such as GPT-3) is anticipated as a next-stage operating platform. The importance of forecasting accuracy and reliability is considered a vital element in guiding technology development to afford stronger contingencies as ideological changes are forecast to expand threats to ecology and earth systems, possibly eclipsing the traditional vulnerabilities of nation states. The early results from the method will be subjected to ground truthing using longitudinal investigation.

Keywords: forecasting, technology futures, uncertainty, complexity

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Authors: N. Seemuang, T. McLeay, T. Slatter

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Worn tools have a direct effect on the surface finish and part accuracy. Tool condition monitoring systems have been developed over a long period and used to avoid a loss of productivity resulting from using a worn tool. However, the majority of tool monitoring research has applied expensive sensing systems not suitable for production. In this work, the cutting sound in turning machine was studied using microphone. Machining trials using seven cutting conditions were conducted until the observable flank wear width (FWW) on the main cutting edge exceeded 0.4 mm. The cutting inserts were removed from the tool holder and the flank wear width was measured optically. A microphone with built-in preamplifier was used to record the machining sound of EN24 steel being face turned by a CNC lathe in a wet cutting condition using constant surface speed control. The sound was sampled at 50 kS/s and all sound signals recorded from microphone were transformed into the frequency domain by FFT in order to establish the frequency content in the audio signature that could be then used for tool condition monitoring. The extracted feature from audio signal was compared to the flank wear progression on the cutting inserts. The spectrogram reveals a promising feature, named as ‘spindle noise’, which emits from the main spindle motor of turning machine. The spindle noise frequency was detected at 5.86 kHz of regardless of cutting conditions used on this particular CNC lathe. Varying cutting speed and feed rate have an influence on the magnitude of power spectrum of spindle noise. The magnitude of spindle noise frequency alters in conjunction with the tool wear progression. The magnitude increases significantly in the transition state between steady-state wear and severe wear. This could be used as a warning signal to prepare for tool replacement or adapt cutting parameters to extend tool life.

Keywords: tool wear, flank wear, condition monitoring, spindle noise

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Authors: Abdullah Bal

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This paper presents a one-class classification (OCC) technique based on Fukunaga-Koontz Transform (FKT) for binary classification problems. The FKT is originally a powerful tool to feature selection and ordering for two-class problems. To utilize the standard FKT for data domain description problem (i.e., one-class classification), in this paper, a set of non-class samples which exist outside of positive class (target class) describing boundary formed with limited training data has been constructed synthetically. The tunnel-like decision boundary around upper and lower border of target class samples has been designed using statistical properties of feature vectors belonging to the training data. To capture higher order of statistics of data and increase discrimination ability, the proposed method, termed one-class FKT (OC-FKT), has been extended to its nonlinear version via kernel machines and referred as OC-KFKT for short. Multiple kernel learning (MKL) is a favorable family of machine learning such that tries to find an optimal combination of a set of sub-kernels to achieve a better result. However, the discriminative ability of some of the base kernels may be low and the OC-KFKT designed by this type of kernels leads to unsatisfactory classification performance. To address this problem, the quality of sub-kernels should be evaluated, and the weak kernels must be discarded before the final decision making process. MKL/OC-FKT and selective MKL/OC-FKT frameworks have been designed stimulated by ensemble learning (EL) to weight and then select the sub-classifiers using the discriminability and diversities measured by eigenvalue ratios. The eigenvalue ratios have been assessed based on their regions on the FKT subspaces. The comparative experiments, performed on various low and high dimensional data, against state-of-the-art algorithms confirm the effectiveness of our techniques, especially in case of small sample size (SSS) conditions.

Keywords: ensemble methods, fukunaga-koontz transform, kernel-based methods, multiple kernel learning, one-class classification

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Authors: S. S. Singh, A. Bhattacharya, S. Bhattacharya

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The eukaryotic exosome complex plays a pivotal role in RNA biogenesis, maturation, surveillance and differential expression of various RNAs in response to varying environmental signals. The exosome is composed of evolutionary conserved nine core subunits and the associated exonucleases Rrp6 and Rrp44. Rrp6p is crucial for the processing of rRNAs, other non-coding RNAs, regulation of polyA tail length and termination of transcription. Rrp6p, a 3’-5’ exonuclease is required for degradation of 5’-external transcribed spacer (ETS) released from the rRNA precursors during the early steps of pre-rRNA processing. In the parasitic protist Entamoeba histolytica in response to growth stress, there occurs the accumulation of unprocessed pre-rRNA and 5’ ETS sub fragment. To understand the processes leading to this accumulation, we looked for Rrp6 and the exosome subunits in E. histolytica, by in silico approaches. Of the nine core exosomal subunits, seven had high percentage of sequence similarity with the yeast and human. The EhRrp6 homolog contained exoribonuclease and HRDC domains like yeast but its N- terminus lacked the PMC2NT domain. EhRrp6 complemented the temperature sensitive phenotype of yeast rrp6Δ cells suggesting conservation of biological activity. We showed 3’-5’ exoribonuclease activity of EhRrp6p with in vitro-synthesized appropriate RNAs substrates. Like the yeast enzyme, EhRrp6p degraded unstructured RNA, but could degrade the stem-loops slowly. Furthermore, immunolocalization revealed that EhRrp6 was nuclear-localized in normal cells but was diminished from nucleus during serum starvation, which could explain the accumulation of 5’ETS during stress. Our study shows functional conservation of EhRrp6p in E.histolytica, an early-branching eukaryote, and will help to understand the evolution of exosomal components and their regulatory function.

Keywords: entamoeba histolytica, exosome complex, rRNA processing, Rrp6

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Authors: Abhilash Sahu, Amit Priyadarshi

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In this paper, we will discuss the existence of weak solutions of the Kirchhoff type boundary value problem on the Sierpinski gasket. Where S denotes the Sierpinski gasket in R² and S₀ is the intrinsic boundary of the Sierpinski gasket. M: R → R is a positive function and h: S × R → R is a suitable function which is a part of our main equation. ∆p denotes the p-Laplacian, where p > 1. First of all, we will define a weak solution for our problem and then we will show the existence of at least two solutions for the above problem under suitable conditions. There is no well-known concept of a generalized derivative of a function on a fractal domain. Recently, the notion of differential operators such as the Laplacian and the p-Laplacian on fractal domains has been defined. We recall the result first then we will address the above problem. In view of literature, Laplacian and p-Laplacian equations are studied extensively on regular domains (open connected domains) in contrast to fractal domains. In fractal domains, people have studied Laplacian equations more than p-Laplacian probably because in that case, the corresponding function space is reflexive and many minimax theorems which work for regular domains is applicable there which is not the case for the p-Laplacian. This motivates us to study equations involving p-Laplacian on the Sierpinski gasket. Problems on fractal domains lead to nonlinear models such as reaction-diffusion equations on fractals, problems on elastic fractal media and fluid flow through fractal regions etc. We have studied the above p-Laplacian equations on the Sierpinski gasket using fibering map technique on the Nehari manifold. Many authors have studied the Laplacian and p-Laplacian equations on regular domains using this Nehari manifold technique. In general Euler functional associated with such a problem is Frechet or Gateaux differentiable. So, a critical point becomes a solution to the problem. Also, the function space they consider is reflexive and hence we can extract a weakly convergent subsequence from a bounded sequence. But in our case neither the Euler functional is differentiable nor the function space is known to be reflexive. Overcoming these issues we are still able to prove the existence of at least two solutions of the given equation.

Keywords: Euler functional, p-Laplacian, p-energy, Sierpinski gasket, weak solution

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Authors: Tambe Daniel Atem

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Background: Clinical Research is an organized research on human beings intended to provide adequate information on the drug use as a therapeutic agent on its safety and efficacy. The significance of the study is to educate the global health and life science graduates in Clinical Research in depth to perform better as it involves testing drugs on human beings. Objectives: to provide an overall understanding of the scientific approach to the evaluation of new and existing medical interventions and to apply ethical and regulatory principles appropriate to any individual research. Methodology: It is based on – Primary data analysis and Secondary data analysis. Primary data analysis: means the collection of data from journals, the internet, and other online sources. Secondary data analysis: a survey was conducted with a questionnaire to interview the Clinical Research Professionals to understand the need of training to perform clinical trials globally. The questionnaire consisted details of the professionals working with the expertise. It also included the areas of clinical research which needed intense training before entering into hardcore clinical research domain. Results: The Clinical Trials market worldwide worth over USD 26 billion and the industry has employed an estimated 2,10,000 people in the US and over 70,000 in the U.K, and they form one-third of the total research and development staff. There are more than 2,50,000 vacant positions globally with salary variations in the regions for a Clinical Research Coordinator. R&D cost on new drug development is estimated at US$ 70-85 billion. The cost of doing clinical trials for a new drug is US$ 200-250 million. Due to an increase trained Clinical Research Professionals India has emerged as a global hub for clinical research. The Global Clinical Trial outsourcing opportunity in India in the pharmaceutical industry increased to more than $2 billion in 2014 due to increased outsourcing from U.S and Europe to India. Conclusion: Assessment of training need is recommended for newer Clinical Research Professionals and trial sites, especially prior the conduct of larger confirmatory clinical trials.

Keywords: clinical research, clinical trials, clinical research professionals

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Authors: Tahani Hallek, Dhaou Akrout, Riadh Ahmadi, Mabrouk Montacer

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The present work is an organic geochemical study of the Fahdene Formation outcrops at the Mahjouba region belonging to the Eastern part of the Kalaat Senan structure in northwestern Tunisia (the Kef-Tedjerouine area). The analytical study of the organic content of the samples collected, allowed us to point out that the Formation in question is characterized by an average to good oil potential. This fossilized organic matter has a mixed origin (type II and III), as indicated by the relatively high values of hydrogen index. This origin is confirmed by the C29 Steranes abundance and also by tricyclic terpanes C19/(C19+C23) and tetracyclic terpanes C24/(C24+C23) ratios, that suggest a marine environment of deposit with high plants contribution. We have demonstrated that the heterogeneity of organic matter between the marine aspect, confirmed by the presence of foraminifera, and the continental contribution, is the result of an episodic anomaly in relation to the sequential stratigraphy. Given that the study area is defined as an outer platform forming a transition zone between a stable continental domain to the south and a deep basin to the north, we have explained the continental contribution by successive forced regressions, having blocked the albian transgression, allowing the installation of the lowstand system tracts. This aspect is represented by the incised valleys filling, in direct contact with the pelagic and deep sea facies. Consequently, the Fahdene Formation, in the Kef-Tedjerouine area, consists of transgressive system tracts (TST) brutally truncated by extras of continental progradation; resulting in a mixed influence deposition having retained a heterogeneous organic material.

Keywords: molecular geochemistry, biomarkers, forced regression, deposit environment, mixed origin, Northern Tunisia

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