Search results for: simulink simulation model

Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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Performance of different filtering approaches depends on modeling of dynamical system and algorithm structure. For modeling and smoothing the data the evaluation of posterior distribution in different filtering approach should be chosen carefully. In this paper different filtering approaches like filter KALMAN, EKF, UKF, EKS and smoother RTS is simulated in some trajectory tracking of path and accuracy and limitation of these approaches are explained. Then probability of model with different filters is compered and finally the effect of the noise variance to estimation is described with simulations results.

Keywords: Gaussian approximation, Kalman smoother, parameter estimation, noise variance

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Authors: Fares Senouci, Bachir Imine

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This document provides numerical and experimental optimization of the aerodynamic performance of a drone equipped with three types of horizontal stabilizer. To build this optimal configuration, an experimental and numerical study was conducted on three parameters: the geometry of the stabilizer (horizontal form or reverse V form), the position of the horizontal stabilizer (up or down), and the landing gear position (closed or open). The results show that up-stabilizer position with respect to the horizontal plane of the fuselage provides better aerodynamic performance, and that the landing gear increases the lift in the zone of stability, that is to say where the flow is not separated.

Keywords: aerodynamics, drag, lift, turbulence model, wind tunnel

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Authors: Jaya Mathew

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Many organizations are faced with the challenge of how to analyze and build Machine Learning models using their sensitive telemetry data. In this paper, we discuss how users can leverage the power of R without having to move their big data around as well as a cloud based solution for organizations willing to host their data in the cloud. By using ScaleR technology to benefit from parallelization and remote computing or R Services on premise or in the cloud, users can leverage the power of R at scale without having to move their data around.

Keywords: predictive maintenance, machine learning, big data, cloud based, on premise solution, R

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Authors: Anoop T. R., Otman Basir, Robert F. Hess, Eileen E. Birch, Brooke A. Koritala, Reed M. Jost, Becky Luu, David Stager, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. We developed a two-stage method for strabismus detection and classification based on photographs of the face. The first stage detects the presence or absence of strabismus, and the second stage classifies the type of strabismus. The first stage comprises face detection using Haar cascade, facial landmark estimation, face alignment, aligned face landmark detection, segmentation of the eye region, and detection of strabismus using VGG 16 convolution neural networks. Face alignment transforms the face to a canonical pose to ensure consistency in subsequent analysis. Using facial landmarks, the eye region is segmented from the aligned face and fed into a VGG 16 CNN model, which has been trained to classify strabismus. The CNN determines whether strabismus is present and classifies the type of strabismus (exotropia, esotropia, and vertical deviation). If stage 1 detects strabismus, the eye region image is fed into stage 2, which starts with the estimation of pupil center coordinates using mask R-CNN deep neural networks. Then, the distance between the pupil coordinates and eye landmarks is calculated along with the angle that the pupil coordinates make with the horizontal and vertical axis. The distance and angle information is used to characterize the degree and direction of the strabismic eye misalignment. This model was tested on 100 clinically labeled images of children with (n = 50) and without (n = 50) strabismus. The True Positive Rate (TPR) and False Positive Rate (FPR) of the first stage were 94% and 6% respectively. The classification stage has produced a TPR of 94.73%, 94.44%, and 100% for esotropia, exotropia, and vertical deviations, respectively. This method also had an FPR of 5.26%, 5.55%, and 0% for esotropia, exotropia, and vertical deviation, respectively. The addition of one more feature related to the location of corneal light reflections may reduce the FPR, which was primarily due to children with pseudo-strabismus (the appearance of strabismus due to a wide nasal bridge or skin folds on the nasal side of the eyes).

Keywords: strabismus, deep neural networks, face detection, facial landmarks, face alignment, segmentation, VGG 16, mask R-CNN, pupil coordinates, angle deviation, horizontal and vertical deviation

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Authors: Marius Sebastian Secula, Mihaela Darie, Gabriela Carja

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Persistent organic pollutant discharged by various industries or urban regions into the aquatic ecosystems represent a serious threat to fauna and human health. The endocrine disrupting compounds are known to have toxic effects even at very low values of concentration. The anti-inflammatory agent Ibuprofen is an endocrine disrupting compound and is considered as model pollutant in the present study. The use of light energy to accomplish the latest requirements concerning wastewater discharge demands highly-performant and robust photo-catalysts. Many efforts have been paid to obtain efficient photo-responsive materials. Among the promising photo-catalysts, layered double hydroxides (LDHs) attracted significant consideration especially due to their composition flexibility, high surface area and tailored redox features. This work presents Fe(II) self-supported on ZnMeLDHs (Me =Al3+, Fe3+) as novel efficient photo-catalysts for Fenton-like catalysis. The co-precipitation method was used to prepare ZnAlLDH, ZnFeAlLDH and ZnCrLDH (Zn2+/Me3+ = 2 molar ratio). Fe(II) was self-supported on the LDHs matrices by using the reconstruction method, at two different values of weight concentration. X-ray diffraction (XRD), thermogravimetric analysis (TG/DTG), Fourier transform infrared (FTIR) and transmission electron microscopy (TEM) were used to investigate the structural, textural, and micromorphology of the catalysts. The Fe(II)/ZnMeLDHs nano-hybrids were tested for the degradation of a model pharmaceutical agent, the anti-inflammatory agent ibuprofen, by photocatalysis and photo-Fenton catalysis, respectively. The results point out that the embedment Fe(II) into ZnFeAlLDH and ZnCrLDH lead to a slight enhancement of ibuprofen degradation by light irradiation, whereas in case of ZnAlLDH, the degradation process is relatively low. A remarkable enhancement of ibuprofen degradation was found in the case of Fe(II)/ZnMeLDHs by photo-Fenton process. Acknowledgements: This work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS - UEFISCDI, project number PN-II-RU-TE-2014-4-0405.

Keywords: layered double hydroxide, heterogeneous Fenton, micropollutant, photocatalysis

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Authors: Mitat Uysal, Aynur Uysal

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Artificial Intelligence (AI) is fundamentally driven by mathematics, with many of its core algorithms rooted in mathematical principles such as linear algebra, probability theory, calculus, and optimization techniques. This paper explores the deep connection between AI and mathematics, highlighting the role of mathematical concepts in key AI techniques like machine learning, neural networks, and optimization. To demonstrate this connection, a case study involving the implementation of a neural network using Python is presented. This practical example illustrates the essential role that mathematics plays in training a model and solving real-world problems.

Keywords: AI, mathematics, machine learning, optimization techniques, image processing

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Authors: Meredith Jones, Susan Catapano, Carol McNulty

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Study abroad experiences create unique learning opportunities for preservice teachers to strengthen their reflective thinking practices through applied learning experiences. Not only do study abroad experiences provide opportunities for students to expand their cultural sensitivity, but incorporating applied learning experiences in study abroad trips creates unique opportunities for preservice teachers to engage in critical reflection on their teaching skills. Applied learning experiences are designed to nurture learning and growth through a reflective, experiential process outside the traditional classroom setting. As students participate in applied learning experiences, they engage in critical reflection independently, with their peers, and with university faculty. Critical reflection within applied learning contexts generates, deepens, and documents learning but must be intentionally designed to be effective. Grounded in Dewey’s model of reflection, this qualitative study examines longitudinal data from various study abroad cohorts from a particular university. Reflective data was collected during the study abroad trip, and follow up data on critical reflection of teaching practices were collected six months and a year after the trip. Dewey’s model of reflection requires preservice teachers to make sense of their experiences by reflecting on theoretical knowledge, experiences, and pedagogical knowledge. Guided reflection provides preservice teachers with a framework to respond to questions and ideas critical to the applied learning outcomes. Prompts are used to engage preservice teachers in reflecting on situations they have experienced and how they can be transferred to their teaching. Findings from this study noted that students with previous field experiences, or work in the field, engaged in more critical reflection on pedagogical knowledge throughout their applied learning experience. Preservice teachers with limited experiences in the field benefited from engaging in critical reflection prompted by university faculty during the applied learning experience. However, they were able to independently engage in critical reflection once they began work in the field through university field placements, internships, or student teaching. Finally, students who participated in study abroad applied learning experiences reported their critical reflection on their teaching practices, and cultural sensitivity enhanced their teaching and relationships with children once they formally entered the teaching profession.

Keywords: applied learning experiences, critical reflection, cultural sensitivity, preservice teachers, teacher education

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Authors: Akhilesh Kumar, Sathyanarayan G., Nirmala S.

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An unusual approach is developed to determine the orbit of satellites/space objects. The determination of orbits is considered a boundary value problem and has been solved using the finite difference method (FDM). Only positions of the satellites/space objects are known at two end times taken as boundary conditions. The technique of finite difference has been used to calculate the orbit between end times. In this approach, the governing equation is defined as the satellite's equation of motion with a perturbed acceleration. Using the finite difference method, the governing equations and boundary conditions are discretized. The resulting system of algebraic equations is solved using Tri Diagonal Matrix Algorithm (TDMA) until convergence is achieved. This methodology test and evaluation has been done using all GPS satellite orbits from National Geospatial-Intelligence Agency (NGA) precise product for Doy 125, 2023. Towards this, two hours of twelve sets have been taken into consideration. Only positions at the end times of each twelve sets are considered boundary conditions. This algorithm is applied to all GPS satellites. Results achieved using FDM compared with the results of NGA precise orbits. The maximum RSS error for the position is 0.48 [m] and the velocity is 0.43 [mm/sec]. Also, the present algorithm is applied on the IRNSS satellites for Doy 220, 2023. The maximum RSS error for the position is 0.49 [m], and for velocity is 0.28 [mm/sec]. Next, a simulation has been done for a Highly Elliptical orbit for DOY 63, 2023, for the duration of 6 hours. The RSS of difference in position is 0.92 [m] and velocity is 1.58 [mm/sec] for the orbital speed of more than 5km/sec. Whereas the RSS of difference in position is 0.13 [m] and velocity is 0.12 [mm/sec] for the orbital speed less than 5km/sec. Results show that the newly created method is reliable and accurate. Further applications of the developed methodology include missile and spacecraft targeting, orbit design (mission planning), space rendezvous and interception, space debris correlation, and navigation solutions.

Keywords: finite difference method, grid generation, NavIC system, orbit perturbation

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Authors: Alona Faktor

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In this work, we present a NN-based computational model that can perform attention shifts according to high-level instruction. The instruction specifies the type of attentional shift using explicit geometrical relation. The instruction also can be of cognitive nature, specifying more complex human-human interaction or human-object interaction, or object-object interaction. Applying this approach sequentially allows obtaining a structural description of an image. A novel data-set of interacting humans and objects is constructed using a computer graphics engine. Using this data, we perform systematic research of relational segmentation shifts.

Keywords: cognitive science, attentin, deep learning, generalization

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Authors: S. Lecheb, A. Chellil, H. Mechakra, S. Attou, H. Kebir

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Although leaf springs are one of the oldest suspension components they are still frequently used, especially in commercial vehicles. Being able to capture the leaf spring characteristics is of significant importance for vehicle handling dynamics studies. The main function of leaf spring is not only to support vertical load but also to isolate road induced vibrations. It is subjected to millions of load cycles leading to fatigue failure. It needs to have excellent fatigue life. The objective of this work is its use of Abaqus software to locate the most stressed areas and predict the areas in which it occurs in fatigue and crack of leaf spring and calculate the stress and frequencies of this model.

Keywords: leaf spring, crack, stress, natural frequencies

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Authors: Jihan Abdulazeez Ahmed, Adnan Mohsin Abdulazeez Brifcani

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This paper suggests a new internal architecture of holon based on feature selection model using the combination of Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is used to generate features while ANN is used as a classifier to evaluate the produced features. Proposed system is applied on the Wine data set, the statistical result proves that the proposed system is effective and has the ability to choose informative features with high accuracy.

Keywords: artificial neural network, bees algorithm, feature selection, Holon

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Authors: Mahdi Hamzehei, Seyyed Amin Hakim, Nahid Taherian

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Fins play an important role in increasing the efficiency of compact shell and tube heat exchangers by increasing heat transfer. The objective of this paper is to determine the optimum fin wave angle, as one of the geometric parameters affecting the efficiency of the heat exchangers. To this end, finite volume method is used to model and simulate the flow in heat exchanger. In this study, computational fluid dynamics simulations of wave channel are done. The results show that the wave angle affects the temperature output of the heat exchanger.

Keywords: fin wave angle, tube, intercooler, optimum, performance

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Authors: Aqsa Jamil, Tamura Hiroshi, Katsuchi Hiroshi, Wang Jiaqi

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The yield point represents the upper limit of forces which can be applied to a specimen without causing any permanent deformation. After yielding, the behavior of the specimen suddenly changes, including the possibility of cracking or buckling. So, the accumulation of damage or type of fracture changes depending on this condition. As it is difficult to accurately detect yield points of the several stress concentration points in structural steel specimens, an effort has been made in this research work to develop a convenient technique using thermography (temperature-based detection) during tensile tests for the precise detection of yield point initiation. To verify the applicability of thermography camera, tests were conducted under different loading conditions and measuring the deformation by installing various strain gauges and monitoring the surface temperature with the help of a thermography camera. The yield point of specimens was estimated with the help of temperature dip, which occurs due to the thermoelastic effect during the plastic deformation. The scattering of the data has been checked by performing a repeatability analysis. The effects of temperature imperfection and light source have been checked by carrying out the tests at daytime as well as midnight and by calculating the signal to noise ratio (SNR) of the noised data from the infrared thermography camera, it can be concluded that the camera is independent of testing time and the presence of a visible light source. Furthermore, a fully coupled thermal-stress analysis has been performed by using Abaqus/Standard exact implementation technique to validate the temperature profiles obtained from the thermography camera and to check the feasibility of numerical simulation for the prediction of results extracted with the help of the thermographic technique.

Keywords: signal to noise ratio, thermoelastic effect, thermography, yield point

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Authors: D. Srinivasacharya, Nidhi Humnekar

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The goal of this research is to numerically investigate the convection of nanofluid flow in an inclined porous channel. Brownian motion and thermophoresis effects are accounted for by nanofluid. In addition, the flow in the porous region governs Brinkman’s equation. The perturbed state of the generalized eigenvalue problem is obtained using normal mode analysis, and Chebyshev spectral collocation was used to solve this problem. For various values of the governing parameters, the critical wavenumber and critical Rayleigh number are calculated, and preferred modes are identified.

Keywords: Brinkman model, inclined channel, nanofluid, linear stability, porous media

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Authors: B. Adini, M. Oren

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Introduction: Communicable diseases and pandemics pose a growing threat to the well-being of the global population. A vital component of protecting the public health is the creation and sustenance of a continuous preparedness for such hazards. A joint Israeli-German task force was deployed in order to develop an advanced tool for self-evaluation of emergency preparedness for variable types of biological threats. Methods: Based on a comprehensive literature review and interviews with leading content experts, an evaluation tool was developed based on quantitative and qualitative parameters and indicators. A modified Delphi process was used to achieve consensus among over 225 experts from both Germany and Israel concerning items to be included in the evaluation tool. Validity and applicability of the tool for medical institutions was examined in a series of simulation and field exercises. Results: Over 115 German and Israeli experts reviewed and examined the proposed parameters as part of the modified Delphi cycles. A consensus of over 75% of experts was attained for 183 out of 188 items. The relative importance of each parameter was rated as part of the Delphi process, in order to define its impact on the overall emergency preparedness. The parameters were integrated in computerized web-based software that enables to calculate scores of emergency preparedness for biological events. Conclusions: The parameters developed in the joint German-Israeli project serve as benchmarks that delineate actions to be implemented in order to create and maintain an ongoing preparedness for biological events. The computerized evaluation tool enables to continuously monitor the level of readiness and thus strengths and gaps can be identified and corrected appropriately. Adoption of such a tool is recommended as an integral component of quality assurance of public health and safety.

Keywords: biological events, emergency preparedness, bioterrorism, natural biological events

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Authors: Zakaria Kharbouch, Mustapha Bouchaara, F. Elkouihen, A. Habbal, A. Ratnani, A. Faik

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Solid-state lithium-ion batteries have garnered increasing interest in modern energy research due to their potential for safer, more efficient, and sustainable energy storage systems. Among the critical components of these batteries, the electrolyte plays a pivotal role, with LLZO garnet-based electrolytes showing significant promise. Garnet materials offer intrinsic advantages such as high Li-ion conductivity, wide electrochemical stability, and excellent compatibility with lithium metal anodes. However, optimizing ionic conductivity in garnet structures poses a complex challenge, primarily due to the multitude of potential dopants that can be incorporated into the LLZO crystal lattice. The complexity of material design, influenced by numerous dopant options, requires a systematic method to find the most effective combinations. This study highlights the utility of machine learning (ML) techniques in the materials discovery process to navigate the complex range of factors in garnet-based electrolytes. Collaborators from the materials science and ML fields worked with a comprehensive dataset previously employed in a similar study and collected from various literature sources. This dataset served as the foundation for an extensive data refinement phase, where meticulous error identification, correction, outlier removal, and garnet-specific feature engineering were conducted. This rigorous process substantially improved the dataset's quality, ensuring it accurately captured the underlying physical and chemical principles governing garnet ionic conductivity. The data refinement effort resulted in a significant improvement in the predictive performance of the machine learning model. Originally starting at an accuracy of 0.32, the model underwent substantial refinement, ultimately achieving an accuracy of 0.88. This enhancement highlights the effectiveness of the interdisciplinary approach and underscores the substantial potential of machine learning techniques in materials science research.

Keywords: lithium batteries, all-solid-state batteries, machine learning, solid state electrolytes

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Authors: Fatbardha Kadiu, Nulifer Caliskan

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The value added tax came as a necessity of substituting the old tax on sales. Based on the advantages of this new tax in our days it is used successfully in more than 140 countries around the world. The aim of the paper is to describe the nature of this tax with its advantages and disadvantages. Also it will describe the way how it functions in most of the European countries and the actual challenges of these countries on value added tax. It will be present the types of goods which are exempt from this tax, the reasons and the consequences of those exemptions. The paper will be based on secondary data taken from respective literature. An econometric model will be present in order to identify the dependence of value tax from other parameters. The analyzing most refers to the two main principles of harmonization and billing on the fiscal system and the ways how to restructures the system in order to minimize the fiscal evasion.

Keywords: value added tax, revenues, complexity, legal uncertainty

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Authors: Sergey Chirun

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Using of a combination of institutional analysis and network access has allowed the author to identify the characteristics of the informal institutions of regional political power and political regimes. According to the author, ‘field’ of activity of post-Soviet regimes, formed under the influence of informal institutions, often contradicts democratic institutional regional changes which are aimed at creating of a legal-rational type of political domination and balanced model of separation of powers. This leads to the gap between the formal structure of institutions and the real nature of power, predetermining the specific character of the existing political regimes.

Keywords: authoritarianism, institutions, political regime, social networks, transformation

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Authors: H. Chabalala, A. Grootboom, M. Tang

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The innovative development, production, and clinical utilisation of African natural medicines requires frameworks from systematisation, innovation, registration. Afrika faces challenges when it comes to these sectors. The opposite is the case as is is evident in ancient Asian (Traditional Chinese Medicine and Indian Ayurveda and Siddha) medical systems, which are interfaced into their respective national health and educational systems. Afrikan Natural Medicines (ANMs) are yet to develop systematisation frameworks, i.e. disease characterisation and medicines classification. This paper explores classical medical systems drawn from Afrikan and Chinese experts in natural medicines. An Afrikological research methodology was used to conduct in-depth interviews with 20 key respondents selected through purposeful sampling technique. Data was summarised into systematisation frameworks for classical disease theories, patient categorisation, medicine classification, aetiology and pathogenesis of disease, diagnosis and prognosis techniques and treatment methods. It was discovered that ancient Afrika had systematic medical cosmologies, remnants of which are evident in most Afrikan cultural health practices. Parallels could be drawn from classical medical concepts of antiquity, like Chinese Taoist and Indian tantric health systems. Data revealed that both the ancient and contemporary ANM systems were based on living medical cosmologies. The study showed that African Natural Healing Systems have etiological systems, general pathogenesis knowledge, differential diagnostic techniques, comprehensive prognosis and holistic treatment regimes. Systematisation models were developed out of these frameworks, and this could be used for evaluation of clinical research, medical application including development of curriculum for high-education. It was envisaged that frameworks will pave way towards the development, production and commercialisation of ANMs. This was piloted in inclusive innovation, technology transfer and commercialisation of South African natural medicines, cosmeceuticals, nutraceuticals and health infusions. The central model presented here in will assist in curriculum development and establishment of Afrikan Medicines Hospitals and Pharmaceutical Industries.

Keywords: African Natural Medicines, Indigenous Knowledge Systems, Medical Cosmology, Clinical Application

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Authors: Paul Rowley, Adam Thirkill, Nick Doylend, Philip Leicester, Becky Gough

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The dynamic performance of all energy generation technologies is impacted to varying degrees by the stochastic properties of the wider system within which the generation technology is located. This stochasticity can include the varying nature of ambient renewable energy resources such as wind or solar radiation, or unpredicted changes in energy demand which impact upon the operational behaviour of thermal generation technologies. An understanding of these stochastic impacts are especially important in contexts such as highly distributed (or embedded) generation, where an understanding of issues affecting the individual or aggregated performance of high numbers of relatively small generators is especially important, such as in ESCO projects. Probabilistic evaluation of monitored or simulated performance data is one technique which can provide an insight into the dynamic performance characteristics of generating systems, both in a prognostic sense (such as the prediction of future performance at the project’s design stage) as well as in a diagnostic sense (such as in the real-time analysis of underperforming systems). In this work, we describe the development, application and outcomes of a new approach to the acquisition of datasets suitable for use in the subsequent performance and impact analysis (including the use of Bayesian approaches) for a number of distributed generation technologies. The application of the approach is illustrated using a number of case studies involving domestic and small commercial scale photovoltaic, solar thermal and natural gas boiler installations, and the results as presented show that the methodology offers significant advantages in terms of plant efficiency prediction or diagnosis, along with allied environmental and social impacts such as greenhouse gas emission reduction or fuel affordability.

Keywords: renewable energy, dynamic performance simulation, Bayesian analysis, distributed generation

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Authors: Kinnsley Travis, Camerron M. Crowder

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Mapk8ip3 (Mitogen-Activated Protein Kinase 8 Interacting Protein 3) is a gene that codes for the JIP3 protein, which is a part of the JIP scaffolding protein family. This protein is involved in axonal vesicle transport, elongation and regeneration. Variants in the Mapk8ip3 gene are associated with a rare-genetic condition that results in a neurodevelopmental disorder that can cause a range of phenotypes including global developmental delay and intellectual disability. Currently, there are 18 known individuals diagnosed to have sequenced confirmed Mapk8ip3 genetic disorders. This project focuses on examining the impact of a subset of missense patient variants on the Jip3 protein function by overexpressing the mRNA of these variants in a zebrafish knockout model for Jip3. Plasmids containing cDNA with individual missense variants were reverse transcribed, purified, and injected into single-cell zebrafish embryos (Wild Type, Jip3 -/+, and Jip3 -/-). At 6-days post mRNA microinjection, morphological, behavioral, and microscopic phenotypes were examined in zebrafish larvae. Morphologically, we compared the size and shape of the zebrafish during their development over a 5-day period. Total locomotive activity was assessed using the Microtracker assay and patterns of movement over time were examined using the DanioVision assay. Lastly, we used confocal microscopy to examine sensory axons for swelling and shortened length, which are phenotypes observed in the loss-of-function knockout Jip3 zebrafish model. Using these assays during embryonic development, we determined the impact of various missense variants on Jip3 protein function, compared to knockout and wild-type zebrafish embryo models. Variants in the gene Mapk8ip3 cause rare-neurodevelopmental disorders due to an essential role in axonal vesicle transport, elongation and regeneration. A subset of missense variants was examined by overexpressing the mRNA of these variants in a Jip3 knock-out zebrafish. Morphological, behavioral, and microscopic phenotypes were examined in zebrafish larvae. Using these assays, the spectrum of disorders can be phenotypically determined and the impact of variant location can be compared to knockout and wild-type zebrafish embryo models.

Keywords: rare disease, neurodevelopmental disorders, mrna overexpression, zebrafish research

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Authors: Yu-Wen Lin, Chin-Sheng Tang, Wan-Yi Chen

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Various biological specimens, drugs, and chemicals exist in the hospital. The medical staffs and hypersensitive inpatients expose might expose to multiple hazards while they work or stay in the hospital. Therefore, the indoor air quality (IAQ) of the hospital should be paid more attention. Respiratory care wards (RCW) are responsible for caring the patients who cannot spontaneously breathe without the ventilators. The patients in RCW are easy to be infected. Compared to the bacteria concentrations of other hospital units, RCW came with higher values in other studies. This research monitored the IAQ of the RCW and checked the compliances of the indoor air quality standards of Taiwan Indoor Air Quality Act. Meanwhile, the influential factors of IAQ and the impacts of ventilator modules, with humidifier or with filter, were investigated. The IAQ of two five-bed wards and one nurse station of a RCW in a regional hospital were monitored. The monitoring was proceeded for 16 hours or 24 hours during the sampling days with a sampling frequency of 20 minutes per hour. The monitoring was performed for two days in a row and the AIQ of the RCW were measured for eight days in total. The concentrations of carbon dioxide (CO₂), carbon monoxide (CO), particulate matter (PM), nitrogen oxide (NOₓ), total volatile organic compounds (TVOCs), relative humidity (RH) and temperature were measured by direct reading instruments. The bioaerosol samples were taken hourly. The hourly air change rate (ACH) was calculated by measuring the air ventilation volume. Human activities were recorded during the sampling period. The linear mixed model (LMM) was applied to illustrate the impact factors of IAQ. The concentrations of CO, CO₂, PM, bacterial and fungi exceeded the Taiwan IAQ standards. The major factors affecting the concentrations of CO, PM₁ and PM₂.₅ were location and the number of inpatients. The significant factors to alter the CO₂ and TVOC concentrations were location and the numbers of in-and-out staff and inpatients. The number of in-and-out staff and the level of activity affected the PM₁₀ concentrations statistically. The level of activity and the numbers of in-and-out staff and inpatients are the significant factors in changing the bacteria and fungi concentrations. Different models of the patients’ ventilators did not affect the IAQ significantly. The results of LMM can be utilized to predict the pollutant concentrations under various environmental conditions. The results of this study would be a valuable reference for air quality management of RCW.

Keywords: respiratory care ward, indoor air quality, linear mixed model, bioaerosol

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Authors: Ulugbek Azimov, Nearchos Stylianidis, Nobuyuki Kawahara, Eiji Tomita

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A chemical kinetics and computational fluid-dynamics (CFD) analysis was performed to evaluate the combustion of syngas derived from biomass and coke-oven solid feedstock in a micro-pilot ignited supercharged dual-fuel engine under lean conditions. For this analysis, a new reduced syngas chemical kinetics mechanism was constructed and validated by comparing the ignition delay and laminar flame speed data with those obtained from experiments and other detail chemical kinetics mechanisms available in the literature. The reaction sensitivity analysis was conducted for ignition delay at elevated pressures in order to identify important chemical reactions that govern the combustion process. The chemical kinetics of NOx formation was analyzed for H2/CO/CO2/CH4 syngas mixtures by using counter flow burner and premixed laminar flame speed reactor models. The new mechanism showed a very good agreement with experimental measurements and accurately reproduced the effect of pressure, temperature and equivalence ratio on NOx formation. In order to identify the species important for NOx formation, a sensitivity analysis was conducted for pressures 4 bar, 10 bar and 16 bar and preheat temperature 300 K. The results show that the NOx formation is driven mostly by hydrogen based species while other species, such as N2, CO2 and CH4, have also important effects on combustion. Finally, the new mechanism was used in a multidimensional CFD simulation to predict the combustion of syngas in a micro-pilot-ignited supercharged dual-fuel engine and results were compared with experiments. The mechanism showed the closest prediction of the in-cylinder pressure and the rate of heat release (ROHR).

Keywords: syngas, chemical kinetics mechanism, internal combustion engine, NOx formation

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Authors: Sendy Ghirardi, Pau Rausell Köster

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The European Commission increasingly pushes cultural policies towards social outcomes and local and regional authorities also call for culture-driven strategies for local development and prosperity and therefore, the measurement of cultural participation becomes increasingly more significant for evidence-based policy-making processes. Cultural participation involves various kinds of social and economic spillovers that combine social and economic objectives of value creation, including social sustainability and respect for human values. Traditionally, from the economic perspective, cultural consumption is measured by the value of financial transactions in purchasing, subscribing to, or renting cultural equipment and content, addressing the market value of cultural products and services. The main sources of data are the household spending survey and merchandise trade survey, among others. However, what characterizes the cultural consumption is that it is linked with the hedonistic and affective dimension rather than the utilitarian one. In fact, nowadays, more and more attention is being paid to the social and psychological dimensions of culture. The aim of this work is to present a comprehensive approach to measure the impacts of cultural participation and cultural users’ behaviour, combining both socio-psychological and economic approaches. The model combines contingent evaluation techniques with the individual characteristic and perception analysis of the cultural experiences to evaluate the cognitive, aesthetic, emotive and social impacts of cultural participation. To investigate the comprehensive approach to measure the impact of the cultural events on individuals, the research has been designed on the basis of prior theoretical development. A deep literature methodology has been done to develop the theoretical model applied to the web platform to measure the impacts of cultural experience on individuals. The developed framework aims to become a democratic tool for evaluating the services that cultural or policy institutions can adopt through the use of an interacting platform that produces big data benefiting academia, cultural management and policies. The Au Culture is a prototype based on an application that can be used on mobile phones or any other digital platform. The development of the AU Culture Platform has been funded by the Valencian Innovation Agency (Government of the Region of Valencia) and it is part of the Horizon 2020 project MESOC.

Keywords: comprehensive approach, cultural participation, economic dimension, socio-psychological dimension

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Authors: Evelyn Nwamaka Ogbeide-Osaretin, Bright Orhewere

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This study examined the role of the population in the linkage between energy consumption and economic development in Nigeria. Time series data on energy consumption, population, and economic development were used for the period 1995 to 2020. The Autoregressive Distributed Lag -Error Correction Model (ARDL-ECM) was engaged. Economic development had a negative substantial impact on energy consumption in the long run. Population growth had a positive significant effect on energy consumption. Government expenditure was also found to impact the level of energy consumption, while energy consumption is not a function of oil price in Nigeria.

Keywords: dynamic analysis, energy consumption, population, economic development, Nigeria

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Authors: Chuping Lo

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This paper presents a simple model demonstrating that ceteris paribus countries with lower barriers to accessing global data tend to earn higher incomes than other countries. Therefore, large countries that inherently have greater data resources tend to have higher incomes than smaller countries, such that the former may be more hesitant than the latter to liberalize cross-border data flows to maintain this advantage. Furthermore, countries with higher artificial intelligence (AI) intensity in production technologies tend to benefit more from economies of scale in data aggregation, leading to higher income and more trade as they are better able to utilize global data.

Keywords: digital intensity, digital divide, international trade, scale of economics

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Authors: Hasmik V. Zanginyan, Gayane S. Ghazaryan, Laura M. Hovsepyan

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Experimental autoimmune encephalomyelitis (EAE) is an inflammatory demyelinating disease of the central nervous system that is induced in laboratory animals by developing an immune response against myelin epitopes. The typical clinical course is ascending palsy, which correlates with inflammation and tissue damage in the thoracolumbar spinal cord, although the optic nerves and brain (especially the subpial white matter and brainstem) are also often affected. With multiple sclerosis, there is a violation of lipid metabolism in myelin. When membrane lipids (glycosphingolipids, phospholipids) are disturbed, metabolites not only play a structural role in membranes but are also sources of secondary mediators that transmit multiple cellular signals. The purpose of this study was to investigate the effect of ganglioside as a therapeutic agent in experimental multiple sclerosis. The biological activity of a ganglioside-containing medicinal preparation (Cronassial) was evaluated in an experimental model of multiple sclerosis in laboratory animals. An experimental model of multiple sclerosis in rats was obtained by immunization with myelin basic protein (MBP), as well as homogenization of the spinal cord or brain. EAE was induced by administering a mixture of an encephalitogenic mixture (EGM) with Complete Freund’s Adjuvant. Mitochondrial fraction was isolated in a medium containing 0,25 M saccharose and 0, 01 M tris buffer, pH - 7,4, by a method of differential centrifugation on a K-24 centrifuge. Glutathione peroxidase activity was assessed by reduction reactions of hydrogen peroxide (H₂O₂) and lipid hydroperoxides (ROOH) in the presence of GSH. LPO activity was assessed by the amount of malondialdehyde (MDA) in the total homogenate and mitochondrial fraction of the spinal cord and brain of control and experimental autoimmune encephalomyelitis rats. MDA was assessed by a reaction with Thiobarbituric acid. For statistical data analysis on PNP, SPSS (Statistical Package for Social Science) package was used. The nature of the distribution of the obtained data was determined by the Kolmogorov-Smirnov criterion. The comparative analysis was performed using a nonparametric Mann-Whitney test. The differences were statistically significant when р ≤ 0,05 or р ≤ 0,01. Correlational analysis was conducted using a nonparametric Spearman test. In the work, refrigeratory centrifuge, spectrophotometer LKB Biochrom ULTROSPECII (Sweden), pH-meter PL-600 mrc (Israel), guanosine, and ATP (Sigma). The study of the process of lipid peroxidation in the total homogenate of the brain and spinal cord in experimental animals revealed an increase in the content of malonic dialdehyde. When applied, Cronassial observed normalization of lipid peroxidation processes. Reactive oxygen species, causing lipid peroxidation processes, can be toxic both for neurons and for oligodendrocytes that form myelin, causing a violation of their lipid composition. The high content of lipids in the brain and the uniqueness of their structure determines the nature of the development of LPO processes. The lipid layer of cellular and intracellular membranes performs two main functions -barrier and matrix (structural). Damage to the barrier leads to dysregulation of intracellular processes and severe disorders of cellular functions.

Keywords: experimental autoimmune encephalomyelitis, multiple sclerosis, neuroinflammation, therapy

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Authors: Humaira M. Khan, Kanwal Asif

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Ischemic stroke is a neurological disorder with a complex pathophysiology associated with motor, sensory and cognitive deficits. Major approaches developed to treat acute ischemic stroke fall into two categories, thrombolysis and neuroprotection. The objectives of this study were to evaluate the neuroprotective and anti-thrombolytic effects of Olea europaea (olive oil) and Malus domestica (apple cider vinegar) and their combination in rat stroke model. Furthermore, histopathological analysis was also performed to assess the severity of ischemia among treated and reference groups. Male albino rats (12 months age) weighing 300- 350gm were acclimatized and subjected to middle cerebral artery occlusion method for stroke induction. Olea europaea and Malus domestica was administered orally in dose of 0.75ml/kg and 3ml/kg and combination was administered at dose of 0.375ml/kg and 1.5ml/kg prophylactically for consecutive 21 days. Negative control group was dosed with normal saline whereas piracetam (250mg/kg) was administered as reference. Neuroprotective activity of standard piracetam, Olea europaea, Malus domestica and their combination was evaluated by performing functional outcome tests i.e. Cylinder, pasta, ladder run, pole and water maize tests. Rats were subjected to surgery after 21 days of treatment for analysis from stroke recovery. Olea europaea and Malus domestica in individual doses of 0.75ml/kg and 3ml/kg respectively showed neuroprotection by significant improvement in ladder run test (121.6± 0.92;128.2 ± 0.73) as compare to reference (125.4 ± 0.74). Both test doses showed significant neuroprotection as compare to reference (9.60 ± 0.50) in pasta test (8.40 ± 0.24;9.80 ± 0.37) whereas with cylinder test, experimental groups showed significant increase in movements (6.60 ± 0.24; 8.40 ± 0.24) in contrast to reference (7.80 ± 0.37).There was a decrease in percentage time taken f to reach the hidden maize in water maize test (56.80 ± 0.58;61.80 ± 0.66) at doses 0.75ml/kg and 3ml/kg respectively as compare to piracetam (59.40 ± 1.07). Olea europaea and Malus domestica individually showed significant reduction in duration of mobility (127.0 ± 0.44; 123.0 ± 0.44) in pole test as compare to piracetam (124.0 ± 0.70). Histopathological analysis revealed the significant extent of protection from ischemia after prophylactic treatments. Hence it is concluded that Olea europaea and Malus domestica are effective neuroprotective agents alone as compare to their combination.

Keywords: ischemia, Malus domestica, neuroprotection, Olea europaea

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Authors: Debanjan Dey, Tamal Banerjee, Kaustubha Mohanty

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Global scalar properties are calculated based on higher occupied molecular orbital (HOMO) and lower unoccupied molecular orbital (LUMO) energy to study the interaction between ionic liquids with Bituminous and Anthracite coal using density function theory (DFT) method. B3LYP/6-31G* calculation predicts HOMO-LUMO energy gap, electronegativity, global hardness, global softness, chemical potential and global softness for individual compounds with their clusters. HOMO-LUMO interaction, electron delocalization, electron donating and accepting is the main source of attraction between individual compounds with their complexes. Cation used in this study: 1-butyl-1-methylpyrrolidinium [BMPYR], 1-methyl -3-propylimmidazolium [MPIM], Tributylmethylammonium [TMA] and Tributylmethylphosphonium [MTBP] with the combination of anion: bis(trifluromethylsulfonyl)imide [Tf2N], methyl carbonate [CH3CO3], dicyanamide [N(CN)2] and methylsulfate [MESO4]. Basically three-tier approach comprising HOMO/LUMO energy, Scalar quantity and infinite dilution activity coefficient (IDAC) by sigma profile generation with COSMO-RS (Conductor like screening model for real solvent) model was chosen for simultaneous interaction. [BMPYR]CH3CO3] (1-butyl-1-methylpyrrolidinium methyl carbonate) and [MPIM][CH3CO3] (1-methyl -3-propylimmidazolium methyl carbonate ) are the best effective ILs on the basis of HOMO-LUMO band gap for Anthracite and Bituminous coal respectively and the corresponding band gap is 0.10137 hartree for Anthracite coal and 0.12485 hartree for Bituminous coal. Further ionic liquids are screened quantitatively with all the scalar parameters and got the same result based on CH-π interaction which is found for HOMO-LUMO gap. To check our findings IDAC were predicted using quantum chemical based COSMO-RS methodology which gave the same trend as observed our scalar quantity calculation. Thereafter a qualitative measurement is doing by sigma profile analysis which gives complementary behavior between IL and coal that means highly miscible with each other.

Keywords: coal-ionic liquids cluster, COSMO-RS, DFT method, HOMO-LUMO interaction

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Authors: Peter Crow

Abstract:

Boards and directors have been subjects of much scholarly research and public interest over several decades, more so since the succession of high profile company failures of the early 2000s. An array of research outputs including information, correlations, descriptions, models, hypotheses and theories have been reported. While some of this research has shed light on aspects of the board–performance relationship and on board tasks and behaviours, the nature and characteristics of the supposed board–performance relationship remain undetermined. That satisfactory explanations of how boards influence company performance have yet to emerge is a significant blind spot. Yet the board is ultimately responsible for company performance, in accordance with the wishes of shareholders. The aim of this paper is to explore corporate governance and board practice through the lens of strategic management, and to take tentative steps towards a new conception of corporate governance. The findings of a recent longitudinal multiple-case study designed to explore the board’s involvement in strategic management are reported. Qualitative and quantitative data was collected from two quasi-public large companies in New Zealand including from first-hand observations of boards in session, semi-structured interviews with chief executives and chairmen and the inspection of company and board documentation. A synthetic timeline framework was used to collate the financial, board structure, board activity and decision-making data, in order to provide a holistic perspective. Decision sequences were identified, and realist techniques of abduction and retroduction were iteratively applied to analyse the multi-year data set. Using several models previously proposed in the literature as a guide, conjectures were formed, tested and refined—the culmination of which was a provisional model of how boards can influence performance via strategic management. The model builds on both existing theoretical perspectives and theoretical models proposed in the corporate governance and strategic management literature. This paper seeks to add to the understanding of how boards can make meaningful contributions to value creation via strategic management, and to comment on the qualities of directors, social interactions in boardrooms and other circumstances within which influence might be possible given the highly contingent relationship between board activity and business performance outcomes.

Keywords: board practice, case study, corporate governance, strategic management

Procedia PDF Downloads 233