Search results for: analytical validation

Authors: Nursuhaili Najwa Masrol, Nur Hafizah Mohammed, Nur Nadhirah Rusyda Rosnan, Vijaya Subramaniam, Sim Choon Cheak

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Replanting in oil palm cultivation is vital to enable the introduction of planting materials and provides an opportunity to improve the road, drainage, terrace design, and planting density. Oil palm replanting is fundamentally necessary every 25 years. The adoption of the digital replanting blueprint is imperative as it can assist the Malaysia Oil Palm industry in addressing challenges such as labour shortages and limited expertise related to replanting tasks. Effective replanting planning should commence at least 6 months prior to the actual replanting process. Therefore, this study will help to plan and design the replanting blueprint with high-precision translation on the ground. With the advancement of geospatial technology, it is now feasible to engage in thoroughly researched planning, which can help maximize the potential yield. A blueprint designed before replanting is to enhance management’s ability to optimize the planting program, address manpower issues, or even increase productivity. In terrace planting blueprints, geographic tools have been utilized to design the roads, drainages, terraces, and planting points based on the ARM standards. These designs are mapped with location information and undergo statistical analysis. The geospatial approach is essential in precision agriculture and ensuring an accurate translation of design to the ground by implementing high-accuracy technologies. In this study, geospatial and remote sensing technologies played a vital role. LiDAR data was employed to determine the Digital Elevation Model (DEM), enabling the precise selection of terraces, while ortho imagery was used for validation purposes. Throughout the designing process, Geographical Information System (GIS) tools were extensively utilized. To assess the design’s reliability on the ground compared with the current conventional method, high-precision GPS instruments like EOS Arrow Gold and HIPER VR GNSS were used, with both offering accuracy levels between 0.3 cm and 0.5cm. Nearest Distance Analysis was generated to compare the design with actual planting on the ground. The analysis revealed that it could not be applied to the roads due to discrepancies between actual roads and the blueprint design, which resulted in minimal variance. In contrast, the terraces closely adhered to the GPS markings, with the most variance distance being less than 0.5 meters compared to actual terraces constructed. Considering the required slope degrees for terrace planting, which must be greater than 6 degrees, the study found that approximately 65% of the terracing was constructed at a 12-degree slope, while over 50% of the terracing was constructed at slopes exceeding the minimum degrees. Utilizing blueprint replanting promising strategies for optimizing land utilization in agriculture. This approach harnesses technology and meticulous planning to yield advantages, including increased efficiency, enhanced sustainability, and cost reduction. From this study, practical implementation of this technique can lead to tangible and significant improvements in agricultural sectors. In boosting further efficiencies, future initiatives will require more sophisticated techniques and the incorporation of precision GPS devices for upcoming blueprint replanting projects besides strategic progression aims to guarantee the precision of both blueprint design stages and its subsequent implementation on the field. Looking ahead, automating digital blueprints are necessary to reduce time, workforce, and costs in commercial production.

Keywords: replanting, geospatial, precision agriculture, blueprint

Procedia PDF Downloads 83

Authors: Quentin C.P. Bourgogne, Vanessa Bouchart, Pierre Chevrier, Emmanuel Dattoli

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This study presents an experimental and theoretical work conducted on a PolyPhenylene Sulfide reinforced with 40%wt of short glass fibers (PPS GF40) and its matrix. Thermoplastics are widely used in the automotive industry to lightweight automotive parts. The replacement of metallic parts by thermoplastics is reaching under-the-hood parts, near the engine. In this area, the parts are subjected to high temperatures and are immersed in cooling liquid. This liquid is composed of water and glycol and can affect the mechanical properties of the composite. The aim of this work was thus to quantify the evolution of mechanical properties of the thermoplastic composite, as a function of temperature and liquid aging effects, in order to develop a reliable design of parts. An experimental campaign in the tensile mode was carried out at different temperatures and for various glycol proportions in the cooling liquid, for monotonic and cyclic loadings on a neat and a reinforced PPS. The results of these tests allowed to highlight some of the main physical phenomena occurring during these solicitations under tough hydro-thermal conditions. Indeed, the performed tests showed that temperature and liquid cooling aging can affect the mechanical behavior of the material in several ways. The more the cooling liquid contains water, the more the mechanical behavior is affected. It was observed that PPS showed a higher sensitivity to absorption than to chemical aggressiveness of the cooling liquid, explaining this dominant sensitivity. Two kinds of behaviors were noted: an elasto-plastic type under the glass transition temperature and a visco-pseudo-plastic one above it. It was also shown that viscosity is the leading phenomenon above the glass transition temperature for the PPS and could also be important under this temperature, mostly under cyclic conditions and when the stress rate is low. Finally, it was observed that soliciting this composite at high temperatures is decreasing the advantages of the presence of fibers. A new phenomenological model was then built to take into account these experimental observations. This new model allowed the prediction of the evolution of mechanical properties as a function of the loading environment, with a reduced number of parameters compared to precedent studies. It was also shown that the presented approach enables the description and the prediction of the mechanical response with very good accuracy (2% of average error at worst), over a wide range of hydrothermal conditions. A temperature-humidity equivalence principle was underlined for the PPS, allowing the consideration of aging effects within the proposed model. Then, a limit of improvement of the reachable accuracy was determinate for all models using this set of data by the application of an artificial intelligence-based model allowing a comparison between artificial intelligence-based models and phenomenological based ones.

Keywords: aging, analytical modeling, mechanical testing, polymer matrix composites, sequential model, thermomechanical

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Authors: Arlinda Memetaj

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A sound system of administrative justice represents a vital element of democratic governance. The proper control of public administration consists not only of a sound civil service framework and legislative oversight, but empowerment of the public and courts to hold public officials accountable for their decision-making through the application of fair administrative procedural rules and the use of appropriate administrative appeals processes and judicial review. The establishment of both effective public administration and administrative justice system has been for a long period of time among the most ‘important and urgent’ final strategic objectives of almost any country in the Balkans region, including Macedonia, Albania and Kosovo. Closely related to this is their common strategic goal to enter the membership in the European Union, which requires fulfilling of many criteria and standards as incorporated in EU acquis communautaire. The latter is presently done with the framework of the Stabilization and Association Agreement which each of these countries has concluded with the EU accordingly. To above aims, each of the three countries has so far adopted a huge series of legislative and strategic documents related to any aspects of their individual administrative justice system. ‘Changes and reforms’ in this field have been thus the most frequent terms being used in any of these countries. The three countries have already established their own national administrative judiciary, while permanently amending their laws on the general administrative procedure introducing thereby considerable innovations concerned. National administrative courts are expected to have crucial important role within the broader judiciary systems-related reforms of these countries; they are designed to check the legality of decisions of the state administration with the aim to guarantee an effective protection of human rights and legitimate interests of private persons through a regular, conform, fast and reasonable judicial administrative process. Further improvements in this field are presently an integral crucial part of all the relevant national strategic documents including the ones on judiciary reform and public administration reform, as adopted by each of the three countries; those strategic documents are designed among others to provide effective protection of their citizens` rights` of administrative justice. On the basis of the later, the paper finally is aimed at highlighting selective common challenges and problems of the three countries on their European road, while claiming (among others) that the current status quo situation in each of them may be overcome only if there is a proper implementation of the administrative courts decisions and a far stricter international monitoring process thereof. A new approach and strong political commitment from the highest political leadership is thus absolutely needed to ensure the principles of transparency, accountability and merit in public administration. The main methods used in this paper include the analytical and comparative ones due to the very character of the paper itself.

Keywords: administrative courts , administrative justice, administrative procedure, benefit, effective administrative justice, human rights, implementation, monitoring, reform

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Authors: H. M. Wilhelm, P. O. Fernandes, L. P. Dill, C. Steffens, K. G. Moscon, S. M. Peres, V. Bender, T. Marchesan, J. B. Ferreira Neto

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Deterioration of insulating oil is a natural process that occurs during transformers operation. However, this process can be accelerated by some factors, such as oxygen, high temperatures, metals and, moisture, which rapidly reduce oil insulating capacity and favor transformer faults. Parts of building materials of a transformer can be degraded and yield soluble compounds and insoluble particles that shorten the equipment life. Physicochemical tests, dissolved gas analysis (including propane, propylene and, butane), volatile and furanic compounds determination, besides quantitative and morphological analyses of particulate are proposed in this study in order to correlate transformers building materials degradation with insulating oil characteristics. The present investigation involves tests of medium temperature overheating simulation by means of an electric resistance wrapped with the following materials immersed in mineral insulating oil: test I) copper, tin, lead and, paper (heated at 350-400 °C for 8 h); test II) only copper (at 250 °C for 11 h); and test III) only paper (at 250 °C for 8 h and at 350 °C for 8 h). A different experiment is the simulation of electric arc involving copper, using an electric welding machine at two distinct energy sets (low and high). Analysis results showed that dielectric loss was higher in the sample of test I, higher neutralization index and higher values of hydrogen and hydrocarbons, including propane and butane, were also observed. Test III oil presented higher particle count, in addition, ferrographic analysis revealed contamination with fibers and carbonized paper. However, these particles had little influence on the oil physicochemical parameters (dielectric loss and neutralization index) and on the gas production, which was very low. Test II oil showed high levels of methane, ethane, and propylene, indicating the effect of metal on oil degradation. CO₂ and CO gases were formed in the highest concentration in test III, as expected. Regarding volatile compounds, in test I acetone, benzene and toluene were detected, which are oil oxidation products. Regarding test III, methanol was identified due to cellulose degradation, as expected. Electric arc simulation test showed the highest oil oxidation in presence of copper and at high temperature, since these samples had huge concentration of hydrogen, ethylene, and acetylene. Particle count was also very high, showing the highest release of copper in such conditions. When comparing high and low energy, the first presented more hydrogen, ethylene, and acetylene. This sample had more similar results to test I, pointing out that the generation of different particles can be the cause for faults such as electric arc. Ferrography showed more evident copper and exfoliation particles than in other samples. Therefore, in this study, by using different combined analytical techniques, it was possible to correlate insulating oil characteristics with possible contaminants, which can lead to transformers failure.

Keywords: Ferrography, gas analysis, insulating mineral oil, particle contamination, transformer failures

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Authors: Keivan Davami, Michael Munther, Lloyd Hackel

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The control of properties and material behavior by implementing thermal-mechanical processes is based on mechanical deformation and annealing according to a precise schedule that will produce a unique and stable combination of grain structure, dislocation substructure, texture, and dispersion of precipitated phases. The authors recently developed a thermal-mechanical technique to stabilize the microstructure of additively manufactured nickel-based superalloys even after exposure to high temperatures. However, the mechanism(s) that controls this stability is still under investigation. Laser peening (LP), also called laser shock peening (LSP), is a shock based (50 ns duration) post-processing technique used for extending performance levels and improving service life of critical components by developing deep levels of plastic deformation, thereby generating high density of dislocations and inducing compressive residual stresses in the surface and deep subsurface of components. These compressive residual stresses are usually accompanied with an increase in hardness and enhance the material’s resistance to surface-related failures such as creep, fatigue, contact damage, and stress corrosion cracking. While the LP process enhances the life span and durability of the material, the induced compressive residual stresses relax at high temperatures (>0.5Tm, where Tm is the absolute melting temperature), limiting the applicability of the technology. At temperatures above 0.5Tm, the compressive residual stresses relax, and yield strength begins to drop dramatically. The principal reason is the increasing rate of solid-state diffusion, which affects both the dislocations and the microstructural barriers. Dislocation configurations commonly recover by mechanisms such as climbing and recombining rapidly at high temperatures. Furthermore, precipitates coarsen, and grains grow; virtually all of the available microstructural barriers become ineffective.Our results indicate that by using “cyclic” treatments with sequential LP and annealing steps, the compressive stresses survive, and the microstructure is stable after exposure to temperatures exceeding 0.5Tm for a long period of time. When the laser peening process is combined with annealing, dislocations formed as a result of LPand precipitates formed during annealing have a complex interaction that provides further stability at high temperatures. From a scientific point of view, this research lays the groundwork for studying a variety of physical, materials science, and mechanical engineering concepts. This research could lead to metals operating at higher sustained temperatures enabling improved system efficiencies. The strengthening of metals by a variety of means (alloying, work hardening, and other processes) has been of interest for a wide range of applications. However, the mechanistic understanding of the often complex processes of interactionsbetween dislocations with solute atoms and with precipitates during plastic deformation have largely remained scattered in the literature. In this research, the elucidation of the actual mechanisms involved in the novel cyclic LP/annealing processes as a scientific pursuit is investigated through parallel studies of dislocation theory and the implementation of advanced experimental tools. The results of this research help with the validation of a novel laser processing technique for high temperature applications. This will greatly expand the applications of the laser peening technology originally devised only for temperatures lower than half of the melting temperature.

Keywords: laser shock peening, mechanical properties, indentation, high temperature stability

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Authors: Sogand Barghi

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The integration of artificial intelligence (AI) in accounting practices is reshaping the landscape of financial management. This paper explores the innovative applications of AI in the realm of accounting, emphasizing its transformative impact on efficiency, accuracy, decision-making, and financial insights. By harnessing AI's capabilities in data analysis, pattern recognition, and automation, accounting professionals can redefine their roles, elevate strategic decision-making, and unlock unparalleled value for businesses. This paper delves into AI-driven solutions such as automated data entry, fraud detection, predictive analytics, and intelligent financial reporting, highlighting their potential to revolutionize the accounting profession. Artificial intelligence has swiftly emerged as a game-changer across industries, and accounting is no exception. This paper seeks to illuminate the profound ways in which AI is reshaping accounting practices, transcending conventional boundaries, and propelling the profession toward a new era of efficiency and insight-driven decision-making. One of the most impactful applications of AI in accounting is automation. Tasks that were once labor-intensive and time-consuming, such as data entry and reconciliation, can now be streamlined through AI-driven algorithms. This not only reduces the risk of errors but also allows accountants to allocate their valuable time to more strategic and analytical tasks. AI's ability to analyze vast amounts of data in real time enables it to detect irregularities and anomalies that might go unnoticed by traditional methods. Fraud detection algorithms can continuously monitor financial transactions, flagging any suspicious patterns and thereby bolstering financial security. AI-driven predictive analytics can forecast future financial trends based on historical data and market variables. This empowers organizations to make informed decisions, optimize resource allocation, and develop proactive strategies that enhance profitability and sustainability. Traditional financial reporting often involves extensive manual effort and data manipulation. With AI, reporting becomes more intelligent and intuitive. Automated report generation not only saves time but also ensures accuracy and consistency in financial statements. While the potential benefits of AI in accounting are undeniable, there are challenges to address. Data privacy and security concerns, the need for continuous learning to keep up with evolving AI technologies, and potential biases within algorithms demand careful attention. The convergence of AI and accounting marks a pivotal juncture in the evolution of financial management. By harnessing the capabilities of AI, accounting professionals can transcend routine tasks, becoming strategic advisors and data-driven decision-makers. The applications discussed in this paper underline the transformative power of AI, setting the stage for an accounting landscape that is smarter, more efficient, and more insightful than ever before. The future of accounting is here, and it's driven by artificial intelligence.

Keywords: artificial intelligence, accounting, automation, predictive analytics, financial reporting

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Authors: Soumya Awasthi

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The spread of radical ideology is possible not merely through public meetings, protests, and mosques but even in schools, seminaries, and madrasas. The rhetoric created around the relationship between religion and conflict has been the primary factor for instigating global conflicts – when religion is used to achieve broader objectives. There have been numerous cases of religion-driven conflict around the world be it the Jewish revolt between 66 AD and 628 AD or the 1119 AD the Crusades revolt or during the Cold War period or the rise of right-wing politics in India. Some of the major developments which reiterate the significance of religion in the contemporary times include: (1) The emergence of theocracy in Iran in 1979 (2) Resurgence of world-wide religious beliefs in post-Soviet space. (3) Emergence of transnational terrorism shaped by twisted depiction of Islam by the self proclaimed protectors of the religion. Therefore this paper is premised in the argument that religion has always found itself on the periphery of the discipline of International Relations (IR), and has received less attention than it deserves. The focus of the topic is on the discourses of ‘Deobandi’ and its impact both on the geopolitics of the region- particularly in India, Pakistan, and Afghanistan- and also at the global level. Discourse is a mechanism in use since time immemorial and has been a key tool to mobilise masses against the ruling authority. With the help of field surveys, qualitative and analytical method of research in religion and international relations, it has been found that they are numerous madrassas that are running illegally and are unregistered. These seminaries are operating in the Khyber-Pakhtunkhwa and Federally Administered Tribal Area (FATA). During the Soviet invasion of Afghanistan in 1979, relation between religion and geopolitics was highlighted when there was a sudden spread of radical ideas, finding support from countries like Saudi Arabia (who funded the campaign) and Pakistan (which organised the Saudi funds and set up training camps, both educational and military). During this period there was a huge influence of Wahabi theology on the madrasas which started with Deoband philosophy and later became a mix of Wahabi (influenced by Ahmad Ibn Hannabal and Ibn Taimmiya) and Deobandi philosophy, tending towards fundamentalism. Later the impact of regional geopolitics had influence on the global geopolitics when the incidents like attack on the US in 2001, bomb blasts in U.K, Indonesia, Turkey, and Israel in 2000s. In the midst of all this, there were several scholars who pointed towards Deobandi Philosophy as one of the drivers in the creation of armed Islamic groups in Pakistan, Afghanistan. Hence this paper will make an attempt to understand the trend as to how Deobandi religious discourses originating from India have changed over the decades, and who the agents of such changes are. It will throw light on Deoband from pre-independence till date to create a narrative around the religious discourses and Deobandi philosophy and its spill over impact on the map of global and regional security.

Keywords: Deobandi School of Thought, radicalization, regional and global geopolitics, religious discourses, Whabi movement

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Authors: Roberta Martino, Viviana Ventre

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Empirical evidence has, over time, confirmed that the behavior of individuals is inconsistent with the descriptions provided by the Discounted Utility Model, an essential reference for calculating the utility of intertemporal prospects. The model assumes that individuals calculate the utility of intertemporal prospectuses by adding up the values of all outcomes obtained by multiplying the cardinal utility of the outcome by the discount function estimated at the time the outcome is received. The trend of the discount function is crucial for the preferences of the decision maker because it represents the perception of the future, and its trend causes temporally consistent or temporally inconsistent preferences. In particular, because different formulations of the discount function lead to various conclusions in predicting choice, the descriptive ability of models with a hyperbolic trend is greater than linear or exponential models. Suboptimal choices from any time point of view are the consequence of this mechanism, the psychological factors of which are encapsulated in the discount rate trend. In addition, analyzing the decision-making process from a psychological perspective, there is an equivalence between the selection of dominated prospects and a degree of impatience that decreases over time. The first part of the paper describes and investigates the anomalies of the discounted utility model by relating the cognitive distortions of the decision-maker to the emotional factors that are generated during the evaluation and selection of alternatives. Specifically, by studying the degree to which impatience decreases, it’s possible to quantify how the psychological and emotional mechanisms of the decision-maker result in a lack of decision persistence. In addition, this description presents inconsistency as the consequence of an inconsistent attitude towards time-delayed choices. The second part of the paper presents an experimental phase in which we show the relationship between inconsistency and impatience in different contexts. Analysis of the degree to which impatience decreases confirms the influence of the decision maker's emotional impulses for each anomaly in the utility model discussed in the first part of the paper. This work provides an application in the field of personalized behavioral finance. Indeed, the numerous behavioral diversities, evident even in the degrees of decrease in impatience in the experimental phase, support the idea that optimal strategies may not satisfy individuals in the same way. With the aim of homogenizing the categories of investors and to provide a personalized approach to advice, the results proven in the experimental phase are used in a complementary way with the information in the field of behavioral finance to implement the Analytical Hierarchy Process model in intertemporal choices, useful for strategic personalization. In the construction of the Analytic Hierarchy Process, the degree of decrease in impatience is understood as reflecting irrationality in decision-making and is therefore used for the construction of weights between anomalies and behavioral traits.

Keywords: analytic hierarchy process, behavioral finance, financial anomalies, impatience, time inconsistency

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Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes

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The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.

Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models

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Authors: Sumeyra Karatas, Veysel Karatas, Reyhan Safak, Gamze Bulut-Ozturk, Ozgul Kartal

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Productive struggle entails a student's cognitive exertion to comprehend mathematical concepts and uncover solutions not immediately apparent. The significance of productive struggle in learning mathematics is accentuated by influential educational theorists, emphasizing its necessity for learning mathematics with understanding. Consequently, supporting productive struggle in learning mathematics is recognized as a high-leverage and effective mathematics teaching practice. In this study, the investigation into the role of productive struggle in learning mathematics led to the development of a comprehensive rubric for productive struggle pedagogy through an exhaustive literature review. The rubric consists of eight primary criteria and 37 sub-criteria, providing a detailed description of teacher actions and pedagogical choices that foster students' productive struggles. These criteria encompass various pedagogical aspects, including task design, tool implementation, allowing time for struggle, posing questions, scaffolding, handling mistakes, acknowledging efforts, and facilitating discussion/feedback. Utilizing this rubric, a team of researchers and teachers designed eight 90-minute lesson plans, employing a productive struggle pedagogy, for a two-week unit on solving systems of linear equations. Simultaneously, another set of eight lesson plans on the same topic, featuring identical content and problems but employing a traditional lecture-and-practice model, was designed by the same team. The objective was to assess the impact of supporting productive struggle on students' mathematics learning, defined by the strands of mathematical proficiency. This quasi-experimental study compares the control group, which received traditional lecture- and practice instruction, with the treatment group, which experienced a productive struggle in pedagogy. Sixty-six 10th and 11th-grade students from two algebra classes, taught by the same teacher at a high school, underwent either the productive struggle pedagogy or lecture-and-practice approach over two-week eight 90-minute class sessions. To measure students' learning, an assessment was created and validated by a team of researchers and teachers. It comprised seven open-response problems assessing the strands of mathematical proficiency: procedural and conceptual understanding, strategic competence, and adaptive reasoning on the topic. The test was administered at the beginning and end of the two weeks as pre-and post-test. Students' solutions underwent scoring using an established rubric, subjected to expert validation and an inter-rater reliability process involving multiple criteria for each problem based on their steps and procedures. An analysis of covariance (ANCOVA) was conducted to examine the differences between the control group, which received traditional pedagogy, and the treatment group, exposed to the productive struggle pedagogy, on the post-test scores while controlling for the pre-test. The results indicated a significant effect of treatment on post-test scores for procedural understanding (F(2, 63) = 10.47, p < .001), strategic competence (F(2, 63) = 9.92, p < .001), adaptive reasoning (F(2, 63) = 10.69, p < .001), and conceptual understanding (F(2, 63) = 10.06, p < .001), controlling for pre-test scores. This demonstrates the positive impact of supporting productive struggle in learning mathematics. In conclusion, the results revealed the significance of the role of productive struggle in learning mathematics. The study further explored the practical application of productive struggle through the development of a comprehensive rubric describing the pedagogy of supporting productive struggle.

Keywords: effective mathematics teaching practice, high school algebra, learning mathematics, productive struggle

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Authors: Moustafa Osman Mohammed

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This paper introduces topological order in descried social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. Topological order is important in describing the physical systems for exploiting optical systems and improving photonic devices. The stats of topological order have some interesting properties of topological degeneracy and fractional statistics that reveal the entanglement origin of topological order, etc. Topological ideas in photonics form exciting developments in solid-state materials, that being; insulating in the bulk, conducting electricity on their surface without dissipation or back-scattering, even in the presence of large impurities. A specific type of autopoiesis system is interrelated to the main categories amongst existing groups of the ecological phenomena interaction social and medical sciences. The hypothesis, nevertheless, has a nonlinear interaction with its natural environment 'interactional cycle' for exchange photon energy with molecules without changes in topology. The engineering topology of a biosensor is based on the excitation boundary of surface electromagnetic waves in photonic band gap multilayer films. The device operation is similar to surface Plasmonic biosensors in which a photonic band gap film replaces metal film as the medium when surface electromagnetic waves are excited. The use of photonic band gap film offers sharper surface wave resonance leading to the potential of greatly enhanced sensitivity. So, the properties of the photonic band gap material are engineered to operate a sensor at any wavelength and conduct a surface wave resonance that ranges up to 470 nm. The wavelength is not generally accessible with surface Plasmon sensing. Lastly, the photonic band gap films have robust mechanical functions that offer new substrates for surface chemistry to understand the molecular design structure and create sensing chips surface with different concentrations of DNA sequences in the solution to observe and track the surface mode resonance under the influences of processes that take place in the spectroscopic environment. These processes led to the development of several advanced analytical technologies: which are; automated, real-time, reliable, reproducible, and cost-effective. This results in faster and more accurate monitoring and detection of biomolecules on refractive index sensing, antibody-antigen reactions with a DNA or protein binding. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other in order to form unique spatial structure and dynamics of biological molecules for providing the environment mutual contribution in investigation of changes due to the pathogenic archival architecture of cell clusters.

Keywords: autopoiesis, photonics systems, quantum topology, molecular structure, biosensing

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Authors: Jie Lin, Yiwen Pan, Li Zhang, Zhangyong Xia

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Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of lipids, immune cells, and extracellular matrix in the arterial walls. This pathological process can lead to the formation of plaques that can obstruct blood flow and trigger various cardiovascular diseases such as heart attack and stroke. The underlying molecular mechanisms still remain unclear, although many studies revealed the dysfunction of endothelial cells, recruitment and activation of monocytes and macrophages, and the production of pro-inflammatory cytokines and chemokines in atherosclerosis. This study aimed to identify hub genes involved in the progression of atherosclerosis and to analyze their biological function in silico, thereby enhancing our understanding of the disease’s molecular mechanisms. Through the analysis of microarray data, we examined the gene expression in media and neo-intima from plaques, as well as distant macroscopically intact tissue, across a cohort of 32 hypertensive patients. Initially, 112 differentially expressed genes (DEGs) were identified. Subsequent immune infiltration analysis indicated a predominant presence of 27 immune cell types in the atherosclerosis group, particularly noting an increase in monocytes and macrophages. In the Weighted gene co-expression network analysis (WGCNA), 10 modules with a minimum of 30 genes were defined as key modules, with blue, dark, Oliver green and sky-blue modules being the most significant. These modules corresponded respectively to monocyte, activated B cell, and activated CD4 T cell gene patterns, revealing a strong morphological-genetic correlation. From these three gene patterns (modules morphology), a total of 2509 key genes (Gene Significance >0.2, module membership>0.8) were extracted. Six hub genes (CD36, DPP4, HMOX1, PLA2G7, PLN2, and ACADL) were then identified by intersecting 2509 key genes, 102 DEGs with lipid-related genes from the Genecard database. The bio-functional analysis of six hub genes was estimated by a robust classifier with an area under the curve (AUC) of 0.873 in the ROC plot, indicating excellent efficacy in differentiating between the disease and control group. Moreover, PCA visualization demonstrated clear separation between the groups based on these six hub genes, suggesting their potential utility as classification features in predictive models. Protein-protein interaction (PPI) analysis highlighted DPP4 as the most interconnected gene. Within the constructed key gene-drug network, 462 drugs were predicted, with ursodeoxycholic acid (UDCA) being identified as a potential therapeutic agent for modulating DPP4 expression. In summary, our study identified critical hub genes implicated in the progression of atherosclerosis through comprehensive bioinformatic analyses. These findings not only advance our understanding of the disease but also pave the way for applying similar analytical frameworks and predictive models to other diseases, thereby broadening the potential for clinical applications and therapeutic discoveries.

Keywords: atherosclerosis, hub genes, drug prediction, bioinformatics

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Authors: Leo Nnamdi Ozurumba-Dwight

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Single-cell genomic analytical systems have proved to be a platform to isolate bulk cells into selected single cells for genomic, proteomic, and related metabolomic studies. This is enabling systematic investigations of the level of heterogeneity in a diverse and wide pool of cell populations. Single cell technologies, embracing techniques such as high parameter flow cytometry, single-cell sequencing, and high-resolution images are playing vital roles in these investigations on messenger ribonucleic acid (mRNA) molecules and related gene expressions in tracking the nature and course of disease conditions. This entails targeted molecular investigations on unit cells that help us understand cell behavoiur and expressions, which can be examined for their health implications on the health state of patients. One of the vital good sides of single-cell RNA sequencing (scRNA seq) is its probing capacity to detect deranged or abnormal cell populations present within homogenously perceived pooled cells, which would have evaded cursory screening on the pooled cell populations of biological samples obtained as part of diagnostic procedures. Despite conduction of just single-cell transcriptome analysis, scRNAseq now permits comparison of the transcriptome of the individual cells, which can be evaluated for gene expressional patterns that depict areas of heterogeneity with pharmaceutical drug discovery and clinical treatment applications. It is vital to strictly work through the tools of investigations from wet lab to bioinformatics and computational tooled analyses. In the precise steps for scRNAseq, it is critical to do thorough and effective isolation of viable single cells from the tissues of interest using dependable techniques (such as FACS) before proceeding to lysis, as this enhances the appropriate picking of quality mRNA molecules for subsequent sequencing (such as by the use of Polymerase Chain Reaction machine). Interestingly, scRNAseq can be deployed to analyze various types of biological samples such as embryos, nervous systems, tumour cells, stem cells, lymphocytes, and haematopoietic cells. In haematopoietic cells, it can be used to stratify acute myeloid leukemia patterns in patients, sorting them out into cohorts that enable re-modeling of treatment regimens based on stratified presentations. In immunotherapy, it can furnish specialist clinician-immunologist with tools to re-model treatment for each patient, an attribute of precision medicine. Finally, the good predictive attribute of scRNAseq can help reduce the cost of treatment for patients, thus attracting more patients who would have otherwise been discouraged from seeking quality clinical consultation help due to perceived high cost. This is a positive paradigm shift for patients’ attitudes primed towards seeking treatment.

Keywords: immunotherapy, transcriptome, re-modeling, mRNA, scRNA-seq

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Authors: Neoclis Hadjigeorgiou, Spyridon Angelopoulos, Evangelos V. Hristoforou, Paul P. Sotiriadis

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The increasing demand for accurate and reliable magnetic measurements over the past decades has paved the way for the development of different types of magnetic sensing systems as well as of more advanced measurement techniques. Anisotropic Magneto Resistance (AMR) sensors have emerged as a promising solution for applications requiring high resolution, providing an ideal balance between performance and cost. However, certain issues of AMR sensors such as non-linear response and measurement noise are rarely discussed in the relevant literature. In this work, an analog closed loop compensation system is proposed, developed and tested as a means to eliminate the non-linearity of AMR response, reduce the 1/f noise and enhance the sensitivity of magnetic sensor. Additional performance aspects, such as cross-axis and hysteresis effects are also examined. This system was analyzed using an analytical model and a P-Spice model, considering both the sensor itself as well as the accompanying electronic circuitry. In addition, a commercial closed loop architecture Flux-Gate sensor (calibrated and certified), has been used for comparison purposes. Three different experimental setups have been constructed for the purposes of this work, each one utilized for DC magnetic field measurements, AC magnetic field measurements and Noise density measurements respectively. The DC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to calibrate and characterize the system under consideration. A high-accuracy DC power supply has been used for providing the operating current to the Helmholtz coils. The results were recorded by a multichannel voltmeter The AC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to examine the effective bandwidth not only of the proposed system but also for the Flux-Gate sensor. A voltage controlled current source driven by a function generator has been utilized for the Helmholtz coil excitation. The result was observed by the oscilloscope. The third experimental apparatus incorporated an AC magnetic shielding construction composed of several layers of electric steel that had been demagnetized prior to the experimental process. Each sensor was placed alone and the response was captured by the oscilloscope. The preliminary experimental results indicate that closed loop AMR response presented a maximum deviation of 0.36% with respect to the ideal linear response, while the corresponding values for the open loop AMR system and the Fluxgate sensor reached 2% and 0.01% respectively. Moreover, the noise density of the proposed close loop AMR sensor system remained almost as low as the noise density of the AMR sensor itself, yet considerably higher than that of the Flux-Gate sensor. All relevant numerical data are presented in the paper.

Keywords: AMR sensor, chopper, closed loop, electronic noise, magnetic noise, memory effects, flux-gate sensor, linearity improvement, sensitivity improvement

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Authors: Mozhdeh Shirinzadeh, Richard Stroetmann

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Orthotropic steel deck bridge consists of a deck plate, longitudinal stiffeners under the deck plate, cross beams and the main longitudinal girders. Due to the several advantages, Orthotropic Steel Deck (OSD) systems have been utilized in many bridges worldwide. The significant feature of this structural system is its high load-bearing capacity while having relatively low dead weight. In addition, cost efficiency and the ability of rapid field erection have made the orthotropic steel deck a popular type of bridge worldwide. However, OSD bridges are highly susceptible to fatigue damage. A large number of welded joints can be regarded as the main weakness of this system. This problem is, in particular, evident in the bridges which were built before 1994 when the fatigue design criteria had not been introduced in the bridge design codes. Recently, an Orthotropic-composite slab (OCS) for road bridges has been experimentally and numerically evaluated and developed at Technische Universität Dresden as a part of AIF-FOSTA research project P1265. The results of the project have provided a solid foundation for the design and analysis of Orthotropic-composite decks with dowel strips as a durable alternative to conventional steel or reinforced concrete decks. In continuation, while using the achievements of that project, the application of a modified Ortho-composite deck for an existing typical OSD bridge is investigated. Composite action is obtained by using rows of dowel strips in a clothoid (CL) shape. Regarding Eurocode criteria for different fatigue detail categories of an OSD bridge, the effect of the proposed modification approach is assessed. Moreover, a numerical parametric study is carried out utilizing finite element software to determine the impact of different variables, such as the size and arrangement of dowel strips, the application of transverse or longitudinal rows of dowel strips, and local wheel loads. For the verification of the simulation technique, experimental results of a segment of an OCS deck are used conducted in project P1265. Fatigue assessment is performed based on the last draft of Eurocode 1993-2 (2024) for the most probable detail categories (Hot-Spots) that have been reported in the previous statistical studies. Then, an analytical comparison is provided between the typical orthotropic steel deck and the modified Ortho-composite deck bridge in terms of fatigue issues and durability. The load-bearing capacity of the bridge, the critical deflections, and the composite behavior are also evaluated and compared. Results give a comprehensive overview of the efficiency of the rehabilitation method considering the required design service life of the bridge. Moreover, the proposed approach is assessed with regard to the construction method, details and practical aspects, as well as the economic point of view.

Keywords: composite action, fatigue, finite element method, steel deck, bridge

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Authors: Mireille Elhajj, Washington Ochieng, Deeph Chana

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The challenges of the rapid growth in the demand for transport has traditionally been seen within the context of the problems of congestion, air quality, climate change, safety, and affordability. However, there are increasing threats including those related to crime such as cyber-attacks that threaten the security of the transport of people and goods. To the best of the authors’ knowledge, this paper presents for the first time, a comprehensive framework for the assessment of the current and future security issues of multi-modal transport systems. The approach or method proposed is based on a structured framework starting with a detailed specification of the transport asset map (transport system architecture), followed by the identification of vulnerabilities. The asset map and vulnerabilities are used to identify the various approaches for exploitation of the vulnerabilities, leading to the creation of a set of threat scenarios. The threat scenarios are then transformed into risks and their categories, and include insights for their mitigation. The consideration of the mitigation space is holistic and includes the formulation of appropriate policies and tactics and/or technical interventions. The quality of the framework is ensured through a structured and logical process that identifies the stakeholders, reviews the relevant documents including policies and identifies gaps, incorporates targeted surveys to augment the reviews, and uses subject matter experts for validation. The approach to categorising security risks is an extension of the current methods that are typically employed. Specifically, the partitioning of risks into either physical or cyber categories is too limited for developing mitigation policies and tactics/interventions for transport systems where an interplay between physical and cyber processes is very often the norm. This interplay is rapidly taking on increasing significance for security as the emergence of cyber-physical technologies, are shaping the future of all transport modes. Examples include: Connected Autonomous Vehicles (CAVs) in road transport; the European Rail Traffic Management System (ERTMS) in rail transport; Automatic Identification System (AIS) in maritime transport; advanced Communications, Navigation and Surveillance (CNS) technologies in air transport; and the Internet of Things (IoT). The framework adopts a risk categorisation scheme that considers risks as falling within the following threat→impact relationships: Physical→Physical, Cyber→Cyber, Cyber→Physical, and Physical→Cyber). Thus the framework enables a more complete risk picture to be developed for today’s transport systems and, more importantly, is readily extendable to account for emerging trends in the sector that will define future transport systems. The framework facilitates the audit and retro-fitting of mitigations in current transport operations and the analysis of security management options for the next generation of Transport enabling strategic aspirations such as systems with security-by-design and co-design of safety and security to be achieved. An initial application of the framework to transport systems has shown that intra-modal consideration of security measures is sub-optimal and that a holistic and multi-modal approach that also addresses the intersections/transition points of such networks is required as their vulnerability is high. This is in-line with traveler-centric transport service provision, widely accepted as the future of mobility services. In summary, a risk-based framework is proposed for use by the stakeholders to comprehensively and holistically assess the security of transport systems. It requires a detailed understanding of the transport architecture to enable a detailed vulnerabilities analysis to be undertaken, creates threat scenarios and transforms them into risks which form the basis for the formulation of interventions.

Keywords: mitigations, risk, transport, security, vulnerabilities

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Authors: Faranak Felfeliyan, Parvaneh Shokrani, Maryam Atarod

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Introduction Using electron beam is widespread in radiotherapy. The main criteria in radiation therapy is to irradiate the tumor volume with maximum prescribed dose and minimum dose to vital organs around it. Using abutting fields is common in radiotherapy. The main problem in using abutting fields is dose inhomogeneity in the junction region. Electron beam divergence and lateral scattering may lead to hot and cold spots in the junction region. One solution for this problem is using of a spoiler to broaden the penumbra and uniform dose in the junction region. The goal of this research was to compare titanium and aluminum effects as a spoiler for dose uniformity achievement in the junction region of oblique electron fields with Monte Carlo simulation. Dose uniformity in the junction region depends on density, scattering power, thickness of the spoiler and the angle between two fields. Materials and Methods In this study, Monte Carlo model of Siemens Primus linear accelerator was simulated for a 5 MeV nominal energy electron beam using manufacture provided specifications. BEAMnrc and EGSnrc user code were used to simulate the treatment head in electron mode (simulation of beam model). The resulting phase space file was used as a source for dose calculations for 10×10 cm2 field size at SSD=100 cm in a 30×30×45 cm3 water phantom using DOSXYZnrc user code (dose calculations). An automatic MP3-M water phantom tank, MEPHYSTO mc2 software platform and a Semi-Flex Chamber-31010 with sensitive vol­ume of 0.125 cm3 (PTW, Freiburg, Germany) were used for dose distribution measurements. Moreover, the electron field size was 10×10 cm2 and SSD=100 cm. Validation of devel­oped beam model was done by comparing the measured and calculated depth and lateral dose distributions (verification of electron beam model). Simulation of spoilers (using SLAB compo­nent module) placed at the end of the electron applicator, was done using previously vali­dated phase space file for a 5 MeV nominal energy and 10×10 cm2 field size (simulation of spoiler). An in-house routine was developed in order to calculate the combined isodose curves re­sulting from the two simulated abutting fields (calculation of dose distribution in abutting electron fields). Results Verification of the developed 5.9 MeV elec­tron beam model was done by comparing the calculated and measured dose distributions. The maximum percentage difference between calculated and measured PDD was 1%, except for the build-up region in which the difference was 2%. The difference between calculated and measured profile was 2% at the edges of the field and less than 1% in other regions. The effect of PMMA, aluminum, titanium and chromium in dose uniformity achievement in abutting normal electron fields with equivalent thicknesses to 5mm PMMA was evaluated. Comparing R90 and uniformity index of different materials, aluminum was chosen as the optimum spoiler. Titanium has the maximum surface dose. Thus, aluminum and titanium had been chosen to use for dose uniformity achievement in oblique electron fields. Using the optimum beam spoiler, junction dose decreased from 160% to 110% for 15 degrees, from 180% to 120% for 30 degrees, from 160% to 120% for 45 degrees and from 180% to 100% for 60 degrees oblique abutting fields. Using Titanium spoiler, junction dose decreased from 160% to 120% for 15 degrees, 180% to 120% for 30 degrees, 160% to 120% for 45 degrees and 180% to 110% for 60 degrees. In addition, penumbra width for 15 degrees, without spoiler in the surface was 10 mm and was increased to 15.5 mm with titanium spoiler. For 30 degrees, from 9 mm to 15 mm, for 45 degrees from 4 mm to 6 mm and for 60 degrees, from 5 mm to 8 mm. Conclusion Using spoilers, penumbra width at the surface increased, size and depth of hot spots was decreased and dose homogeneity improved at the junc­tion of abutting electron fields. Dose at the junction region of abutting oblique fields was improved significantly by using spoiler. Maximum dose at the junction region for 15⁰, 30⁰, 45⁰ and 60⁰ was decreased about 40%, 60%, 40% and 70% respectively for Titanium and about 50%, 60%, 40% and 80% for Aluminum. Considering significantly decrease in maximum dose using titanium spoiler, unfortunately, dose distribution in the junction region was not decreased less than 110%.

Keywords: abutting fields, electron beam, radiation therapy, spoilers

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Authors: Mayoorika Shukla, Pramila Jakhar, Tejendra Dixit, I. A. Palani, Vipul Singh

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Biosensors are analytical devices with wide range of applications in biological, chemical, environmental and clinical analysis. It comprises of bio-recognition layer which has biomolecules (enzymes, antibodies, DNA, etc.) immobilized over it for detection of analyte and transducer which converts the biological signal into the electrical signal. The performance of biosensor primarily the depends on the bio-recognition layer and therefore it has to be chosen wisely. In this regard, nanostructures of metal oxides such as ZnO, SnO2, V2O5, and TiO2, etc. have been explored extensively as bio-recognition layer. Recently, ZnO has the attracted attention of researchers due to its unique properties like high iso-electric point, biocompatibility, stability, high electron mobility and high electron binding energy, etc. Although there have been many reports on usage of ZnO as bio-recognition layer but to the authors’ knowledge, none has ever observed correlation between optical properties like defect suppression and biosensing capability of the sensor. Here, ZnO nanorods (ZNR) have been synthesized by a low cost, simple and low-temperature hydrothermal growth process, over Platinum (Pt) coated glass substrate. The ZNR have been synthesized in two steps viz. initially a seed layer was coated over substrate (Pt coated glass) followed by immersion of it into nutrient solution of Zinc nitrate and Hexamethylenetetramine (HMTA) with in situ addition of KMnO4. The addition of KMnO4 was observed to have a profound effect over the growth rate anisotropy of ZnO nanostructures. Clustered and powdery growth of ZnO was observed without addition of KMnO4, although by addition of it during the growth, uniform and crystalline ZNR were found to be grown over the substrate. Moreover, the same has resulted in suppression of defects as observed by Normalized Photoluminescence (PL) spectra since KMnO4 is a strong oxidizing agent which provides an oxygen rich growth environment. Further, to explore the correlation between defect suppression and biosensing capability of the ZNR Glucose oxidase (Gox) was immobilized over it, using physical adsorption technique followed by drop casting of nafion. Here the main objective of the work was to analyze effect of defect suppression over biosensing capability, and therefore Gox has been chosen as model enzyme, and electrochemical amperometric glucose detection was performed. The incorporation of KMnO4 during growth has resulted in variation of optical and charge transfer properties of ZNR which in turn were observed to have deep impact on biosensor figure of merits. The sensitivity of biosensor was found to increase by 12-18 times, due to variations introduced by addition of KMnO4 during growth. The amperometric detection of glucose in continuously stirred buffer solution was performed. Interestingly, defect suppression has been observed to contribute towards the improvement of biosensor performance. The detailed mechanism of growth of ZNR along with the overall influence of defect suppression on the sensing capabilities of the resulting enzymatic electrochemical biosensor and different figure of merits of the biosensor (Glass/Pt/ZNR/Gox/Nafion) will be discussed during the conference.

Keywords: biosensors, defects, KMnO4, ZnO nanorods

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Authors: Agnes Siwi Purwaning Tyas, Dewi Cahya Ambarwati

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This paper concerns the language learning that develops as a habit formation and a constructive process while exercising an oppressive power to construct the learners. As a locus of discussion, the investigation problematizes the transfer of English language to Indonesian students of junior high school through the use of English textbooks ‘Real Time: An Interactive English Course for Junior High School Students Year VII-IX’. English language has long performed as a global language and it is a demand upon the non-English native speakers to master the language if they desire to become internationally recognized individuals. Generally, English teachers teach the language in accordance with the nature of language learning in which they are trained and expected to teach the language within the culture of the target language. This provides a potential soft cultural penetration of a foreign ideology through language transmission. In the context of Indonesia, learning English as international language is considered dilemmatic. Most English textbooks in Indonesia incorporate cultural elements of the target language which in some extent may challenge the sensitivity towards local cultural values. On the other hand, local teachers demand more English textbooks for junior high school students which can facilitate cultural dissemination of both local and global values and promote learners’ cultural traits of both cultures to avoid misunderstanding and confusion. It also aims to support language learning as bidirectional process instead of instrument of oppression. However, sensitizing and localizing this foreign language is not sufficient to restrain its soft infiltration. In due course, domination persists making the English language as an authoritative language and positioning the locality as ‘the other’. Such critical premise has led to a discursive analysis referring to how the cultural elements of the target language are presented in the textbooks and whether the local characteristics of Indonesia are able to gradually reduce the degree of the foreign oppressive ideology. The three textbooks researched were written by non-Indonesian author edited by two Indonesia editors published by a local commercial publishing company, PT Erlangga. The analytical elaboration examines the cultural characteristics in the forms of names, terminologies, places, objects and imageries –not the linguistic aspect– of both cultural domains; English and Indonesia. Comparisons as well as categorizations were made to identify the cultural traits of each language and scrutinize the contextual analysis. In the analysis, 128 foreign elements and 27 local elements were found in textbook for grade VII, 132 foreign elements and 23 local elements were found in textbook for grade VIII, while 144 foreign elements and 35 local elements were found in grade IX textbook, demonstrating the unequal distribution of both cultures. Even though the ideal pedagogical approach of English learning moves to a different direction by the means of inserting local elements, the learners are continuously imposed to the culture of the target language and forced to internalize the concept of values under the influence of the target language which tend to marginalize their native culture.

Keywords: bidirectional process, English, local culture, oppression

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Authors: Natalia V. Minaeva, Natalia A. Zorina, Marina N. Khorobrikh, Philipp S. Sherstnev, Tatiana V. Krivokorytova, Alexander S. Luchinin, Maksim S. Minaev, Igor V. Paramonov

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Background. Over the last few decades, the Center for International Blood and Marrow Transplant Research (CIBMTR) and the World Marrow Donor Association (WMDA) have been actively working to ensure the safety of the hematopoietic stem cell (HSC) donation process. Registration of adverse events that may occur during the donation period and establishing a relationship between donation and side effects are included in the WMDA international standards. The level of blood serum N-terminal pro-brain natriuretic peptide (NT-proBNP) is an early marker of myocardial stress. Due to the high analytical sensitivity and specificity, laboratory assessment of NT-proBNP makes it possible to objectively diagnose myocardial dysfunction. It is well known that the main stimulus for proBNP synthesis and secretion from atrial and ventricular cardiac myocytes is myocyte stretch and increasement of myocardial extensibility and pressure in the heart chambers. Аim. The aim of the study was to assess the dynamic changes in the levels of blood serum N-terminal pro-brain natriuretic peptide of unrelated donors at various stages of hematopoietic stem cell mobilization. Materials. We have examined 133 unrelated donors, including 92 men and 41 women, that have been included into the study. The NT-proBNP levels were measured before the start of mobilization, then on the day of apheresis, and after the donation of allogeneic HSC. The relationship between NT-proBNP levels and body mass index (BMI), ferritin, hemoglobin, and white blood cells (WBC) levels was assessed on the day of apheresis. The median age of donors was 34 years. Mobilization of HSCs was managed with filgrastim administration at a dose of 10 μg/kg daily for 4-5 days. The first leukocytapheresis was performed on day 4 from the start of filgrastim administration. Quantitative values of the blood serum NT-proBNP level are presented as a median (Me), first and third quartiles (Q1-Q3). Comparative analysis was carried out using the t-test and correlation analysis as well by Spearman method. Results. The baseline blood serum NT-proBNP levels in all 133 donors were within the reference values (<125 pg/ml) and equaled 21,6 (10,0; 43,3) pg/ml. At the same time, the level of NT-proBNP in women was significantly higher than that of men. On the day of the HSC apheresis, a significant increase of blood serum NT-proBNP levels was detected and equald 131,2 (72,6; 165,3) pg/ml (p<0,001), with higher rates in female donors. A statistically significant weak inverse correleation was established between the level of NT-proBNP and the BMI of donors (-0.18, p = 0,03), as well as the level of hemoglobin (-0.33, p <0,001), and ferritin levels (-0.19, p = 0,03). No relationship has been established between the magnitude of WBC levels achieved as a result of the mobilization of HSC on the day of leukocytapheresis. A day after the apheresis, the blood serum NT-proBNP levels still exceeded the reference values, but there was a decreasing tendency. Conclusion. An increase of the blood serum NT-proBNP level in unrelated donors during the mobilization of HSC was established. Future studies should clarify the reason for this phenomenon, as well as its effects on donors' long-term health.

Keywords: unrelated donors, mobilization, hematopoietic stem cells, N-terminal pro-brain natriuretic peptide

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Authors: Mohammed Makki, Milad Showkatbakhsh, Aiman Tabony

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Computational applications of natural evolutionary processes as problem-solving tools have been well established since the mid-20th century. However, their application within architecture and design has only gained ground in recent years, with an increasing number of academics and professionals in the field electing to utilize evolutionary computation to address problems comprised from multiple conflicting objectives with no clear optimal solution. Recent advances in computer science and its consequent constructive influence on the architectural discourse has led to the emergence of multiple algorithmic processes capable of simulating the evolutionary process in nature within an efficient timescale. Many of the developed processes of generating a population of candidate solutions to a design problem through an evolutionary based stochastic search process are often driven through the application of both environmental and architectural parameters. These methods allow for conflicting objectives to be simultaneously, independently, and objectively optimized. This is an essential approach in design problems with a final product that must address the demand of a multitude of individuals with various requirements. However, one of the main challenges encountered through the application of an evolutionary process as a design tool is the ability for the simulation to maintain variation amongst design solutions in the population while simultaneously increasing in fitness. This is most commonly known as the ‘golden rule’ of balancing exploration and exploitation over time; the difficulty of achieving this balance in the simulation is due to the tendency of either variation or optimization being favored as the simulation progresses. In such cases, the generated population of candidate solutions has either optimized very early in the simulation, or has continued to maintain high levels of variation to which an optimal set could not be discerned; thus, providing the user with a solution set that has not evolved efficiently to the objectives outlined in the problem at hand. As such, the experiments presented in this paper seek to achieve the ‘golden rule’ by incorporating a mathematical fitness criterion for the development of an urban tissue comprised from the superblock as its primary architectural element. The mathematical value investigated in the experiments is the standard deviation factor. Traditionally, the standard deviation factor has been used as an analytical value rather than a generative one, conventionally used to measure the distribution of variation within a population by calculating the degree by which the majority of the population deviates from the mean. A higher standard deviation value delineates a higher number of the population is clustered around the mean and thus limited variation within the population, while a lower standard deviation value is due to greater variation within the population and a lack of convergence towards an optimal solution. The results presented will aim to clarify the extent to which the utilization of the standard deviation factor as a fitness criterion can be advantageous to generating fitter individuals in a more efficient timeframe when compared to conventional simulations that only incorporate architectural and environmental parameters.

Keywords: architecture, computation, evolution, standard deviation, urban

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Authors: D. Mulligan, D. Casey

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Introductory Statement: Delegation is when a registered nurse (RN) transfers a task or activity that is normally within their scope of practice to another person (delegatee). RN delegation is common practice with unregistered staff, e.g., student nurses and health care assistants (HCAs). As the role of the HCA is increasingly embedded as a direct care and support role, especially in long-term residential care for older adults, there is RN uncertainty as to their role as a delegator. The assignment is when a task is transferred to a person that is within the role specification of the delegatee. RNs in long-term care (LTC) for older people are increasingly working in teams where there are less RNs and more HCAs providing direct care to the residents. The RN is responsible and accountable for their decision to delegate and assign tasks to HCAs. In an interpretive, multiple case studies to explore how delegation of tasks by RNs to HCAs occurred in long-term care settings in Ireland the importance of the RN understanding their scope of practice emerged. Methodology: Focus group interviews and individual interviews were undertaken as part of a multiple case study. Both cases, anonymized as Case A and Case B, were within the public health service in Ireland. The case study sites were long-term care settings for older adults located in different social care divisions, and in different geographical areas. Four focus group interviews with staff nurses and three individual interviews with CNMs were undertaken. The interactive data analysis approach was the analytical framework used, with within-case and cross-case analysis. The theoretical lens of organizational role theory, applying the role episode model (REM), was used to understand, interpret, and explain the findings. Study Findings: RNs and CNMs understood the role of the nurse regulator and the scope of practice. RNs understood that the RN was accountable for the care and support provided to residents. However, RNs and CNM2s could not describe delegation in the context of their scope of practice. In both cases, the RNs did not have a standardized process for assessing HCA competence to undertake nursing tasks or interventions. RNs did not routinely supervise HCAs. Tasks were assigned and not delegated. There were differences between the cases in relation to understanding which nursing tasks required delegation. HCAs in Case A undertook clinical vital sign assessments and documentation. HCAs in Case B did not routinely undertake these activities. Delegation and assignment were influenced by the organizational factors, e.g., model of care, absence of delegation policies, inadequate RN education on delegation, and a lack of RN and HCA role clarity. Concluding Statement: Nurse staffing levels and skill mix in long-term care settings continue to change with more HCAs providing more direct care and support. With decreasing RN staffing levels RNs will be required to delegate and assign more direct care to HCAs. There is a requirement to distinguish between RN assignment and delegation at policy, regulation, and organizational levels.

Keywords: assignment, delegation, registered nurse, scope of practice

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Authors: My T. Truong

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Among various professional development (PD) options available for English as a second language (ESL) teachers, especially those at the tertiary level, research engagement has been recently recommended as an innovative model with a transformative force for both individual teachers’ PD and wider school improvement. Teachers who conduct research themselves tend to develop critical and analytical thinking about their instructional practices, and enhance their ability to make autonomous pedagogical judgments and decisions. With such capabilities, teacher researchers are thus more likely to contribute to curriculum innovation of their schools and improvement of the whole educational process. The extent to which ESL teachers are engaged in research, however, depends largely on their research motivation, which can not only decide teachers’ choice of a PD activity to pursue but also affect the degree and duration of effort they are willing to invest in pursuing it. To understand language teachers’ research practices, and to inform educational authorities about ways to promote research culture among their ESL teaching staff, it is therefore vital to investigate teachers’ research motivation. Despite its importance as such, this individual difference construct has not been paid due attention especially in the ESL contexts. To fill this gap, this study aims to explore Vietnamese tertiary ESL teachers’ motivations towards research. Guided by the self-determination theory and the process model of motivation, it investigates teachers’ initial motivations for conducting research, and the factors that sustained or degraded their motivation during the research engagement process. Adopting a qualitative case-study approach, the study collected longitudinal data via semi-structured interviews and guided diary entries from three ESL tertiary teachers who were conducting their own research project. The respondents attended two semi-structured interviews (one at the beginning of their project, and the other one three months afterwards); and wrote six guided diary entries between the two interviews. The results confirm the significant role motivation plays in driving teachers to initiate and maintain their participation in research, and challenge some common assumptions in teacher motivation literature. For instance, the quality of the past and actual research experience unsurprisingly emerged as an important factor that both motivated and demotivated teachers in their research engagement process. Unlike general suggestions in the motivation literature however, external demand was found in this study to be a critical motivation sustaining factor while intrinsic research interest actually did not suffice to help a teacher fulfil his research endeavor. With such findings, the study is expected to widen the motivational perspective in understanding language teacher research practice given the paucity of related studies. Practically, it is hoped to enable teacher educators, PD program designers and educational policy makers in Vietnam and similar contexts to approach the question of whether and how to promote research activities among ESL teachers feasibly. For practicing and in-service teachers, the findings may elucidate to them the motivational conditions in which they can be research engaged, and the motivational factors that might hinder or encourage them in so doing.

Keywords: teacher motivation, teacher professional development, teacher research engagement, English as a second language (ESL)

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Authors: Sameerah A. Al-Hariri Al-Zahrani

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The current study aims at getting acquainted with the impact of the use of some multiple intelligence-based teaching strategies on developing moral intelligence and inferential jurisprudential thinking among secondary school female students. The study has endeavored to answer the following questions: What is the impact of the use of some multiple intelligence-based teaching strategies on developing inferential jurisprudential thinking and moral intelligence among first-year secondary school female students? In the frame of this main research question, the study seeks to answer the following sub-questions: (i) What are the inferential jurisprudential thinking skills among first-year secondary school female students? (ii) What are the components of moral intelligence among first year secondary school female students? (iii) What is the impact of the use of some multiple intelligence‐based teaching strategies (such as the strategies of analyzing values, modeling, Socratic discussion, collaborative learning, peer collaboration, collective stories, building emotional moments, role play, one-minute observation) on moral intelligence among first-year secondary school female students? (iv) What is the impact of the use of some multiple intelligence‐based teaching strategies (such as the strategies of analyzing values, modeling, Socratic discussion, collaborative learning, peer collaboration, collective stories, building emotional moments, role play, one-minute observation) on developing the capacity for inferential jurisprudential thinking of juristic rules among first-year secondary school female students? The study has used the descriptive-analytical methodology in surveying, analyzing, and reviewing the literature on previous studies in order to benefit from them in building the tools of the study and the materials of experimental treatment. The study has also used the experimental method to study the impact of the independent variable (multiple intelligence strategies) on the two dependent variables (moral intelligence and inferential jurisprudential thinking) in first-year secondary school female students’ learning. The sample of the study is made up of 70 female students that have been divided into two groups: an experimental group consisting of 35 students who have been taught through multiple intelligence strategies, and a control group consisting of the other 35 students who have been taught normally. The two tools of the study (inferential jurisprudential thinking test and moral intelligence scale) have been implemented on the two groups as a pre-test. The female researcher taught the experimental group and implemented the two tools of the study. After the experiment, which lasted eight weeks, was over, the study showed the following results: (i) The existence of significant statistical differences (0.05) between the mean average of the control group and that of the experimental group in the inferential jurisprudential thinking test (recognition of the evidence of jurisprudential rule, recognition of the motive for the jurisprudential rule, jurisprudential inferencing, analogical jurisprudence) in favor of the experimental group. (ii) The existence of significant statistical differences (0.05) between the mean average of the control group and that of the experimental group in the components of the moral intelligence scale (sympathy, conscience, moral wisdom, tolerance, justice, respect) in favor of the experimental group. The study has, thus, demonstrated the impact of the use of some multiple intelligence-based teaching strategies on developing moral intelligence and inferential jurisprudential thinking.

Keywords: moral intelligence, teaching, inferential jurisprudential thinking, secondary school

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Authors: Ziara Carmelli G. Tan, Irene Carmelle S. Tan

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Background: Trichotillomania (TTM) and Major Depressive Disorder (MDD) are two psychiatric conditions that frequently co-occur, presenting a significant challenge for treatment due to their complex interplay. TTM involves repetitive hair-pulling, leading to noticeable hair loss and distress, while MDD is characterized by persistent low mood and loss of interest or pleasure, leading to dysfunctionality. This case report examines the intricate relationship between TTM and MDD in a young adult female, emphasizing the need for a comprehensive, multifaceted therapeutic approach to address both disorders effectively. Case Presentation: The patient is a 21-year-old female college student and youth church leader who presented with chronic hair-pulling and depressive symptoms. Her premorbid personality was marked by low self-esteem and a strong need for external validation. Despite her academic and social responsibilities and achievements, she struggled with managing her emotional distress, which was exacerbated by her family dynamics and her role within her church community. Her hair-pulling and mood symptoms were particularly triggered by self-esteem threats and feelings of inadequacy. She was diagnosed with Trichotillomania, Scalp and Major Depressive Disorder. Intervention/Management: The patient’s treatment plan was comprehensive, incorporating both pharmacological and non-pharmacological interventions. Initial pharmacologic management was Fluoxetine 20mg/day up, titrated to 40mg/day with no improvement; hence, shifted to Escitalopram 20mg/day and started with N-acetylcysteine 600mg/day with noted significant improvement in symptoms. Psychotherapeutic strategies played a crucial role in her treatment. These included supportive-expressive psychodynamic psychotherapy, which helped her explore and understand underlying emotional conflicts. Cognitive-behavioral techniques were employed to modify her maladaptive thoughts and behaviors. Grief processing was integrated to help her cope with significant losses. Family therapy was done to address conflicts and collaborate with the treatment process. Psychoeducation was provided to enhance her understanding of her condition and to empower her in her treatment journey. A suicide safety plan was developed to ensure her safety during critical periods. An interprofessional approach, which involved coordination with the Dermatology service for co-management, was also a key component of her treatment. Outcome: Over the course of 15 therapy sessions, the patient demonstrated significant improvement in both her depressive symptoms and hair-pulling behavior. Her active engagement in therapy, combined with pharmacological support, facilitated better emotional regulation and a more cohesive sense of self. Her adherence to the treatment plan, along with the collaborative efforts of the interprofessional team, contributed to her positive outcomes. Discussion: This case underscores the significance of addressing both TTM and its comorbid conditions to achieve effective treatment outcomes. The intricate interplay between TTM and MDD in the patient’s case highlights the importance of a comprehensive treatment plan that includes both pharmacological and psychotherapeutic approaches. Supportive-expressive psychodynamic psychotherapy, Cognitive-behavioral techniques, and Family therapy were particularly beneficial in addressing the complex emotional and behavioral aspects of her condition. The involvement of an interprofessional team, including dermatology co-management, was crucial in providing holistic care. Future practice should consider the benefits of such a multidisciplinary approach to managing complex cases like this, ensuring that both the psychological and physiological aspects of the disorders are adequately addressed.

Keywords: cognitive-behavioral therapy, interprofessional approach, major depressive disorder, psychodynamic psychotherapy, trichotillomania

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Authors: Tibor Ajtai, Noémi Utry, Máté Pintér, Tomi Smausz, Zoltán Kónya, Béla Hopp, Gábor Szabó, Zoltán Bozóki

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Characterization of spectral responses of light absorbing carbonaceous particulate matter (LAC) is of great importance in both modelling its climate effect and interpreting remote sensing measurement data. The residential or domestic combustion of coal is one of the dominant LAC constituent. According to some related assessments the residential coal burning account for roughly half of anthropogenic BC emitted from fossil fuel burning. Despite of its significance in climate the comprehensive investigation of optical properties of residential coal aerosol is really limited in the literature. There are many reason of that starting from the difficulties associated with the controlled burning conditions of the fuel, through the lack of detailed supplementary proximate and ultimate chemical analysis enforced, the interpretation of the measured optical data, ending with many analytical and methodological difficulties regarding the in-situ measurement of coal aerosol spectral responses. Since the gas matrix of ambient can significantly mask the physicochemical characteristics of the generated coal aerosol the accurate and controlled generation of residential coal particulates is one of the most actual issues in this research area. Most of the laboratory imitation of residential coal combustion is simply based on coal burning in stove with ambient air support allowing one to measure only the apparent spectral feature of the particulates. However, the recently introduced methodology based on a laser ablation of solid coal target opens up novel possibilities to model the real combustion procedure under well controlled laboratory conditions and makes the investigation of the inherent optical properties also possible. Most of the methodology for spectral characterization of LAC is based on transmission measurement made of filter accumulated aerosol or deduced indirectly from parallel measurements of scattering and extinction coefficient using free floating sampling. In the former one the accuracy while in the latter one the sensitivity are liming the applicability of this approaches. Although the scientific community are at the common platform that aerosol-phase PhotoAcoustic Spectroscopy (PAS) is the only method for precise and accurate determination of light absorption by LAC, the PAS based instrumentation for spectral characterization of absorption has only been recently introduced. In this study, the investigation of the inherent, spectral features of laser generated and chemically characterized residential coal aerosols are demonstrated. The experimental set-up and its characteristic for residential coal aerosol generation are introduced here. The optical absorption and the scattering coefficients as well as their wavelength dependency are determined by our state-of-the-art multi wavelength PAS instrument (4λ-PAS) and multi wavelength cosinus sensor (Aurora 3000). The quantified wavelength dependency (AAE and SAE) are deduced from the measured data. Finally, some correlation between the proximate and ultimate chemical as well as the measured or deduced optical parameters are also revealed.

Keywords: absorption, scattering, residential coal, aerosol generation by laser ablation

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Authors: B. Neethu, Diptesh Das

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The present study investigates the performance of a semi-active controller using magneto-rheological dampers (MR) for seismic response reduction of a multi-span bridge. The application of structural control to the structures during earthquake excitation involves numerous challenges such as proper formulation and selection of the control strategy, mathematical modeling of the system, uncertainty in system parameters and noisy measurements. These problems, however, need to be tackled in order to design and develop controllers which will efficiently perform in such complex systems. A control algorithm, which can accommodate un-certainty and imprecision compared to all the other algorithms mentioned so far, due to its inherent robustness and ability to cope with the parameter uncertainties and imprecisions, is the sliding mode algorithm. A sliding mode control algorithm is adopted in the present study due to its inherent stability and distinguished robustness to system parameter variation and external disturbances. In general a semi-active control scheme using an MR damper requires two nested controllers: (i) an overall system controller, which derives the control force required to be applied to the structure and (ii) an MR damper voltage controller which determines the voltage required to be supplied to the damper in order to generate the desired control force. In the present study a sliding mode algorithm is used to determine the desired optimal force. The function of the voltage controller is to command the damper to produce the desired force. The clipped optimal algorithm is used to find the command voltage supplied to the MR damper which is regulated by a semi active control law based on sliding mode algorithm. The main objective of the study is to propose a robust semi active control which can effectively control the responses of the bridge under real earthquake ground motions. Lumped mass model of the bridge is developed and time history analysis is carried out by solving the governing equations of motion in the state space form. The effectiveness of MR dampers is studied by analytical simulations by subjecting the bridge to real earthquake records. In this regard, it may also be noted that the performance of controllers depends, to a great extent, on the characteristics of the input ground motions. Therefore, in order to study the robustness of the controller in the present study, the performance of the controllers have been investigated for fourteen different earthquake ground motion records. The earthquakes are chosen in such a way that all possible characteristic variations can be accommodated. Out of these fourteen earthquakes, seven are near-field and seven are far-field. Also, these earthquakes are divided into different frequency contents, viz, low-frequency, medium-frequency, and high-frequency earthquakes. The responses of the controlled bridge are compared with the responses of the corresponding uncontrolled bridge (i.e., the bridge without any control devices). The results of the numerical study show that the sliding mode based semi-active control strategy can substantially reduce the seismic responses of the bridge showing a stable and robust performance for all the earthquakes.

Keywords: bridge, semi active control, sliding mode control, MR damper

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Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Loretta Ichim, Dan Popescu, Grigore Stamatescu

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The paper reports the collaboration between a top university from Romania and three companies for the implementation of a research project in a multidisciplinary domain, focusing on the impact and benefits both for the education and industry. The joint activities were developed under the Space Technology and Advanced Research Program (STAR), funded by the Romanian Space Agency (ROSA) for a university-industry partnership. The context was defined by linking the European Space Agency optional programs, with the development and promotion national research, with the educational and industrial capabilities in the aeronautics, security and related areas by increasing the collaboration between academic and industrial entities as well as by realizing high-level scientific production. The project name is Multisensory Robotic System for Aerial Monitoring of Critical Infrastructure Systems (MUROS), which was carried 2013-2016. The project included the University POLITEHNICA of Bucharest (coordinator) and three companies, which manufacture and market unmanned aerial systems. The project had as main objective the development of an integrated system for combined ground wireless sensor networks and UAV monitoring in various application scenarios for critical infrastructure surveillance. This included specific activities related to fundamental and applied research, technology transfer, prototype implementation and result dissemination. The core area of the contributions laid in distributed data processing and communication mechanisms, advanced image processing and embedded system development. Special focus is given by the paper to analyzing the impact the project implementation in the educational process, directly or indirectly, through the faculty members (professors and students) involved in the research team. Three main directions are discussed: a) enabling students to carry out internships at the partner companies, b) handling advanced topics and industry requirements at the master's level, c) experiments and concept validation for doctoral thesis. The impact of the research work (as the educational component) developed by the faculty members on the increasing performances of the companies’ products is highlighted. The collaboration between university and companies was well balanced both for contributions and results. The paper also presents the outcomes of the project which reveals the efficient collaboration between high education and industry: master thesis, doctoral thesis, conference papers, journal papers, technical documentation for technology transfer, prototype, and patent. The experience can provide useful practices of blending research and education within an academia-industry cooperation framework while the lessons learned represent a starting point in debating the new role of advanced research and development performing companies in association with higher education. This partnership, promoted at UE level, has a broad impact beyond the constrained scope of a single project and can develop into long-lasting collaboration while benefiting all stakeholders: students, universities and the surrounding knowledge-based economic and industrial ecosystem. Due to the exchange of experiences between the university (UPB) and the manufacturing company (AFT Design), a new project, SIMUL, under the Bridge Grant Program (Romanian executive agency UEFISCDI) was started (2016 – 2017). This project will continue the educational research for innovation on master and doctoral studies in MUROS thematic (collaborative multi-UAV application for flood detection).

Keywords: education process, multisensory robotic system, research and innovation project, technology transfer, university-industry partnership

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Authors: Abdulkadir Sarauta

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Almost every type of industrial process involves the release of trace quantity of toxic organic and inorganic compound that up in receiving water bodies, this study was aimed at assessing the Persistent Organic Pollutant Level in Challawa River Basin of Kano State, Nigeria. And the research formed the basis of identifying the presence of PCBs and PAHs in receiving water bodies in the study area, assessing the PCBs and PAHs concentration in receiving water body of Challawa system, evaluate the concentration level of PCBs and PAHs in fishes in the study area, determine the concentration level of PCBs and PAHs in crops irrigated in the study area as well as compare the concentration of PCBs and PAHs with the acceptable limit set by Nigerian, EU, U.S and WHO standard. Data were collected using reconnaissance survey, site inspection, field survey, laboratory experiment as well as secondary data source. A total of 78 samples were collected through stratified systematic random sampling (i.e., 26 samples for each of water, crops and fish) three sampling points were chosen and designated A, B and C along the stretch of the river (i.e. up, middle, and downstream) from Yan Danko Bridge to Tambirawa bridge. The result shows that the Polychlorinated biphenyls (PCBs) was not detected while, polycyclic aromatic hydrocarbons (PAHs) was detected in the whole samples analysed at the trench of Challawa River basin in order to assess the contribution of human activities to global environmental pollution. The total concentrations of ΣPAH and ΣPCB ranges between 0.001 to 0.087mg/l and 0.00 to 0.00mg/l of water samples While, crops samples ranges between 2.0ppb to 8.1ppb and fish samples ranges from 2.0 to 6.7ppb.The whole samples are polluted because most of the parameters analyzed exceed the threshold limits set by WHO, Nigerian, U.S and EU standard. The analytical results revealed that some chemicals are present in water, crops and fishes are significantly very high at Zamawa village which is very close to Challawa industrial estate and also is main effluent discharge point and drinking water around study area is not potable for consumption. Analysis of Variance was obtained by Bartlett’s test performance. There is only significant difference in water because the P < 0.05 level of significant, But there is no difference in crops concentration they have the same performance, likes wise in the fishes. It is said to be of concern to health hazard which will increase incidence of tumor related diseases such as skin, lungs, bladder, gastrointestinal cancer, this show there is high failure of pollution abatement measures in the area. In conclusion, it can be said that industrial activities and effluent has impact on Challawa River basin and its environs especially those that are living in the immediate surroundings. Arising from the findings of this research some recommendations were made the industries should treat their liquid properly by installing modern treatment plants.

Keywords: Challawa River Basin, organic, persistent, pollutant

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