Search results for: efficiency analysis and selection bias

Authors: Omar Romero-Hernandez, Federico Castillo, Armando Sanchez, Sergio Romero, Andrea Romero, Michael Mitchell

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Environmental policies for resource conservation in rural areas include subsidies on services and social programs to cover living expenses. Government's expectation is that rural communities who benefit from social programs, such as payment for ecosystem services, are provided with an incentive to conserve natural resources and preserve natural sinks for greenhouse gases. At the same time, global climate change has affected the lives of people worldwide. The capability to adapt to global warming depends on the available resources and the standard of living, putting rural communities at a disadvantage. This paper explores whether rural entrepreneurship can represent a solution to resource conservation and global warming adaptation in rural communities. The research focuses on a sample of two coffee communities in Oaxaca, Mexico. Researchers used geospatial information contained in aerial photographs of the geographical areas of interest. Households were identified in the photos via the roofs of households and georeferenced via coordinates. From the household population, a random selection of roofs was performed and received a visit. A total of 112 surveys were completed, including questions of socio-demographics, perception to climate change and adaptation activities. The population includes two groups of study: entrepreneurs and non-entrepreneurs. Data was sorted, filtered, and validated. Analysis includes descriptive statistics for exploratory purposes and a multi-regression analysis. Outcomes from the surveys indicate that coffee farmers, who demonstrate entrepreneurship skills and hire employees, are more eager to adapt to climate change despite the extreme adverse socioeconomic conditions of the region. We show that farmers with entrepreneurial tendencies are more creative in using innovative farm practices such as the planting of shade trees, the use of live fencing, instead of wires, and watershed protection techniques, among others. This result counters the notion that small farmers are at the mercy of climate change and have no possibility of being able to adapt to a changing climate. The study also points to roadblocks that farmers face when coping with climate change. Among those roadblocks are a lack of extension services, access to credit, and reliable internet, all of which reduces access to vital information needed in today’s constantly changing world. Results indicate that, under some circumstances, funding and supporting entrepreneurship programs may provide more benefit than traditional social programs.

Keywords: entrepreneurship, global warming, rural communities, climate change adaptation

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Authors: A. G. Akhundov

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Issues of obtaining unbiased data on the status of pipeline systems of oil- and oil product transportation become especially important when laying and operating pipelines under severe nature and climatic conditions. The essential attention is paid here to researching exogenous processes and their impact on linear facilities of the pipeline system. Reliable operation of pipelines under severe nature and climatic conditions, timely planning and implementation of compensating measures are only possible if operation conditions of pipeline systems are regularly monitored, and changes of permafrost soil and hydrological operation conditions are accounted for. One of the main reasons for emergency situations to appear is the geodynamic factor. Emergency situations are proved by the experience to occur within areas characterized by certain conditions of the environment and to develop according to similar scenarios depending on active processes. The analysis of natural and technical systems of main pipelines at different stages of monitoring gives a possibility of making a forecast of the change dynamics. The integration of GIS technologies, traditional means of geotechnical monitoring (in-line inspection, geodetic methods, field observations), and remote methods (aero-visual inspection, aero photo shooting, air and ground laser scanning) provides the most efficient solution of the problem. The united environment of geo information system (GIS) is a comfortable way to implement the monitoring system on the main pipelines since it provides means to describe a complex natural and technical system and every element thereof with any set of parameters. Such GIS enables a comfortable simulation of main pipelines (both in 2D and 3D), the analysis of situations and selection of recommendations to prevent negative natural or man-made processes and to mitigate their consequences. The specifics of such systems include: a multi-dimensions simulation of facilities in the pipeline system, math modelling of the processes to be observed, and the use of efficient numeric algorithms and software packets for forecasting and analyzing. We see one of the most interesting possibilities of using the monitoring results as generating of up-to-date 3D models of a facility and the surrounding area on the basis of aero laser scanning, data of aerophotoshooting, and data of in-line inspection and instrument measurements. The resulting 3D model shall be the basis of the information system providing means to store and process data of geotechnical observations with references to the facilities of the main pipeline; to plan compensating measures, and to control their implementation. The use of GISs for geotechnical monitoring of pipeline systems is aimed at improving the reliability of their operation, reducing the probability of negative events (accidents and disasters), and at mitigation of consequences thereof if they still are to occur.

Keywords: databases, 3D GIS, geotechnical monitoring, pipelines, laser scaning

Procedia PDF Downloads 192

Authors: Peerawat Khongkliang, Prawit Kongjan, Tsuyoshi Imai, Poonsuk Prasertsan, Sompong O-Thong

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A two-stage thermophilic fermentation and electrohydrogenesis process was used to convert cassava starch processing wastewater into hydrogen gas. Maximum hydrogen yield from fermentation stage by Thermoanaerobacterium thermosaccharolyticum PSU-2 was 248 mL H2/g-COD at optimal pH of 6.5. Optimum hydrogen production rate of 820 mL/L/d and yield of 200 mL/g COD was obtained at HRT of 2 days in fermentation stage. Cassava starch processing wastewater fermentation effluent consisted of acetic acid, butyric acid and propionic acid. The effluent from fermentation stage was used as feedstock to generate hydrogen production by microbial electrolysis cell (MECs) at an applied voltage of 0.6 V in second stage with additional 657 mL H2/g-COD was produced. Energy efficiencies based on electricity needed for the MEC were 330 % with COD removals of 95 %. The overall hydrogen yield was 800-900 mL H2/g-COD. Microbial community analysis of electrohydrogenesis by DGGE shows that exoelectrogens belong to Acidiphilium sp., Geobacter sulfurreducens and Thermincola sp. were dominated at anode. These results show two-stage thermophilic fermentation, and electrohydrogenesis process improved hydrogen production performance with high hydrogen yields, high gas production rates and high COD removal efficiency.

Keywords: cassava starch processing wastewater, biohydrogen, thermophilic fermentation, microbial electrolysis cell

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Authors: E. Botchway, C. Godfrey, V. Anderson, C. Catroppa

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Introduction: Sleep disturbances are common after childhood traumatic brain injury (TBI). This systematic review aimed to assess the prevalence, types, and predictors of sleep disturbances in childhood TBI. Methods: Medline, Pubmed, PsychInfo, Web of Science, and EMBASE databases were searched. Out of the 547 articles assessed, 15 met selection criteria for this review. Results: Sleep disturbances were common in children and adolescents with TBI, irrespective of injury severity. Excessive daytime sleepiness and insomnia were the most common sleep disturbances reported. Sleep disturbance was predicted by sex, injury severity, pre-existing sleep disturbances, younger age, pain, and high body mass index. Conclusions: Sleep disturbances are highly prevalent in childhood TBI, regardless of the injury severity. Routine assessment of sleep in survivors of childhood TBI is recommended.

Keywords: traumatic brain injury, sleep diatiurbances, childhood, systematic review

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Authors: Victor William Harris

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Objective. This study examined the impact of the Positive Behavioral Management Skills (PBMS) online educational program on participants (n = 624) in a Southeastern region of the United States. The PBMS program incorporates established positive psychology behavioral management principles with new research-based practices designed to promote healthy and satisfying relationships between adults and children while constructively managing and preventing problematic behavior. Additionally, the PBMS program assists parents and teachers in recognizing the motivations behind a wide range of misbehaviors. The program also offers to forewarn some of the most common mistakes (or “parent traps”) in child behavioral management and describes how they can be avoided. It also describes how to recognize and capitalize on “teachable moments,” which are indispensable in the developmental process. Design. A retrospective-pre-test-then-post-test design was used to reduce response shift bias when assessing knowledge and skill intervention outcomes for twenty-two behavioral management variables. Results. The PBMS program was shown to be effective for increasing knowledge and skills related to managing misbehavior while reinforcing interpersonal relationships and fostering a sense of responsibility and capability within the child. Large standardized mean effect size changes from before to after program intervention was documented for PBMS participants on all twenty-two variables studied. Conclusion. The PBMS program showed initial positive outcomes to assist participants in the sample studied to increase their knowledge and skills in managing child behavior successfully. Implications for parents, educators and practitioners are discussed.

Keywords: behavioral management, discipline, parent education, positive parenting, positive psychology-parenting

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Authors: Kwan Hee Han

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External environment of enterprise is rapidly changing majorly by global competition, cost reduction pressures, and new technology. In these situations, production scheduling function plays a critical role to meet customer requirements and to attain the goal of operational efficiency. It deals with short-term decision making in the production process of the whole supply chain. The major task of production scheduling is to seek a balance between customer orders and limited resources. In manufacturing companies, this task is so difficult because it should efficiently utilize resource capacity under the careful consideration of many interacting constraints. At present, many computerized software solutions have been utilized in many enterprises to generate a realistic production schedule to overcome the complexity of schedule generation. However, most production scheduling systems do not provide sufficient information about the validity of the generated schedule except limited statistics. Process mining only recently emerged as a sub-discipline of both data mining and business process management. Process mining techniques enable the useful analysis of a wide variety of processes such as process discovery, conformance checking, and bottleneck analysis. In this study, the performance of generated production schedule is evaluated by mining event log data of production scheduling software system by using the process mining techniques since every software system generates event logs for the further use such as security investigation, auditing and error bugging. An application of process mining approach is proposed for the validation of the goodness of production schedule generated by scheduling software systems in this study. By using process mining techniques, major evaluation criteria such as utilization of workstation, existence of bottleneck workstations, critical process route patterns, and work load balance of each machine over time are measured, and finally, the goodness of production schedule is evaluated. By using the proposed process mining approach for evaluating the performance of generated production schedule, the quality of production schedule of manufacturing enterprises can be improved.

Keywords: data mining, event log, process mining, production scheduling

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Authors: Anderson Braga Mendes, Wallington Felipe de Almeida, Cicero Medeiros da Silva

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This study aimed to assess the lifespan of the fish transposition system of the Itaipu Power Plant (Brazil/Paraguay) by using 3D hydrodynamic modeling and Churchill trapping effiency in order to identify the sedimentological equilibrium configuration in the main pond of the Piracema Channel, which is part of a 10 km hydraulic circuit that enables fish migration from downstream to upstream (and vice-versa) the Itaipu Dam, overcoming a 120 m water drop. For that, bottom data from 2002 (its opening year) and 2015 were collected and analyzed, besides bed material at 12 stations to the purpose of identifying their granulometric profiles. The Shields and Yalin and Karahan diagrams for initiation of motion of bed material were used to determine the critical bed shear stress for the sedimentological equilibrium state based on the sort of sediment (grain size) to be found at the bottom once the balance is reached. Such granulometry was inferred by analyzing the grosser material (fine and medium sands) which inflows the pond and deposits in its backwater zone, being adopted a range of diameters within the upper and lower limits of that sand stratification. The software Delft 3D was used in an attempt to compute the bed shear stress at every station under analysis. By modifying the input bathymetry of the main pond of the Piracema Channel so as to the computed bed shear stress at each station fell within the intervals of acceptable critical stresses simultaneously, it was possible to foresee the bed configuration of the main pond when the sedimentological equilibrium is reached. Under such condition, 97% of the whole pond capacity will be silted, and a shallow water course with depths ranging from 0.2 m to 1.5 m will be formed; in 2002, depths ranged from 2 m to 10 m. Out of that water path, the new bottom will be practically flat and covered by a layer of water 0.05 m thick. Thus, in the future the main pond of the Piracema Channel will lack its purpose of providing a resting place for migrating fish species, added to the fact that it may become an insurmountable barrier for medium and large sized specimens. Everything considered, it was estimated that its lifespan, from the year of its opening to the moment of the sedimentological equilibrium configuration, will be approximately 95 years–almost half of the computed lifespan of Itaipu Power Plant itself. However, it is worth mentioning that drawbacks concerning the silting in the main pond will start being noticed much earlier than such time interval owing to the reasons previously mentioned.

Keywords: 3D hydrodynamic modeling, Churchill trapping efficiency, fish crossing system, Itaipu power plant, lifespan, sedimentological equilibrium

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Authors: Ayten Ekin Meşe, Selahattin Şentürk, Melike Duvanoğlu

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Petroleum refineries are a highly complex process industry with continuous production and high operating costs. Physical separation of crude oil starts with the crude oil distillation unit, continues with various conversion and purification units, and passes through many stages until obtaining the final product. To meet the desired product specification, process parameters are strictly followed. To be able to ensure the quality of distillates, routine analyses are performed in quality control laboratories based on appropriate international standards such as American Society for Testing and Materials (ASTM) standard methods and European Standard (EN) methods. The cut point of distillates in the crude distillation unit is very crucial for the efficiency of the upcoming processes. In order to maximize the process efficiency, the determination of the quality of distillates should be as fast as possible, reliable, and cost-effective. In this sense, an alternative study was carried out on the crude oil distillation unit that serves the entire refinery process. In this work, studies were conducted with three different crude oil distillates which are Light Straight Run Naphtha (LSRN), Heavy Straight Run Naphtha (HSRN), and Kerosene. These products are named after separation by the number of carbons it contains. LSRN consists of five to six carbon-containing hydrocarbons, HSRN consist of six to ten, and kerosene consists of sixteen to twenty-two carbon-containing hydrocarbons. Physical properties of three different crude distillation unit products (LSRN, HSRN, and Kerosene) were determined using Near-Infrared Spectroscopy with multivariate calibration. The absorbance spectra of the petroleum samples were obtained in the range from 10000 cm⁻¹ to 4000 cm⁻¹, employing a quartz transmittance flow through cell with a 2 mm light path and a resolution of 2 cm⁻¹. A total of 400 samples were collected for each petroleum sample for almost four years. Several different crude oil grades were processed during sample collection times. Extended Multiplicative Signal Correction (EMSC) and Savitzky-Golay (SG) preprocessing techniques were applied to FT-NIR spectra of samples to eliminate baseline shifts and suppress unwanted variation. Two different multivariate calibration approaches (Partial Least Squares Regression, PLS and Genetic Inverse Least Squares, GILS) and an ensemble model were applied to preprocessed FT-NIR spectra. Predictive performance of each multivariate calibration technique and preprocessing techniques were compared, and the best models were chosen according to the reproducibility of ASTM reference methods. This work demonstrates the developed models can be used for routine analysis instead of conventional analytical methods with over 90% accuracy.

Keywords: crude distillation unit, multivariate calibration, near infrared spectroscopy, data preprocessing, refinery

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Authors: Kajingulu Malandala, Ranganai Edmore

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The asymmetric Laplace distribution (ADL) is commonly used as the likelihood function of the Bayesian quantile regression, and it offers different families of likelihood method for quantile regression. Notwithstanding their popularity and practicality, ADL is not smooth and thus making it difficult to maximize its likelihood. Furthermore, Bayesian inference is time consuming and the selection of likelihood may mislead the inference, as the Bayes theorem does not automatically establish the posterior inference. Furthermore, ADL does not account for greater skewness and Kurtosis. This paper develops a new aspect of quantile regression approach for count data based on inverse of the cumulative density function of the Poisson, binomial and Delaporte distributions using the integrated nested Laplace Approximations. Our result validates the benefit of using the integrated nested Laplace Approximations and support the approach for count data.

Keywords: quantile regression, Delaporte distribution, count data, integrated nested Laplace approximation

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Authors: Shishen Xie, Yingda L. Xie

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Tuberculosis (TB) is a potentially serious infectious disease that remains a health concern. The Interferon Gamma Release Assay (IGRA) is a blood test to find out if an individual is tuberculous positive or negative. This study applies statistical analysis to the clinical data of interferon-gamma levels of seventy-three subjects who diagnosed pulmonary TB in an anti-tuberculous treatment. Data analysis is performed to determine if there is a significant decline in interferon-gamma levels for the subjects during a period of six months, and to infer if the anti-tuberculous treatment is effective.

Keywords: data analysis, interferon gamma release assay, statistical methods, tuberculosis infection

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Authors: Theddeus Tochukwu Akano, Omotayo Abayomi Fakinlede

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Proper understanding of the behavior of compliant mechanisms use by athletes is important in order to avoid catastrophic failure. Such compliant mechanisms like the flex-run require the knowledge of their dynamic response and deformation behavior under quickly varying loads. The modeling of finite deformations of the compliant athletic system is described by Neo-Hookean model under contact-impact conditions. The dynamic impact-contact governing equations for both the target and impactor are derived based on the updated Lagrangian approach. A method where contactor and target are considered as a united body is applied in the formulation of the principle of virtual work for the bodies. In this paper, methods of continuum mechanics and nonlinear finite element method were deployed to develop a model that could capture the behavior of the compliant athletic system under quickly varying loads. A hybrid system of symbolic algebra (AceGEN) and a compiled back end (AceFEM) were employed, leveraging both ease of use and computational efficiency. The simulated results reveal the effect of the various contact-impact conditions on the deformation behavior of the impacting compliant mechanism.

Keywords: eigenvalue problems, finite element method, robin boundary condition, sturm-liouville problem

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Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman

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In this study, a multivariate analysis of potato spectroscopic data was presented to detect the presence of brown rot disease or not. Near-Infrared (NIR) spectroscopy (1,350-2,500 nm) combined with multivariate analysis was used as a rapid, non-destructive technique for the detection of brown rot disease in potatoes. Spectral measurements were performed in 565 samples, which were chosen randomly at the infection place in the potato slice. In this study, 254 infected and 311 uninfected (brown rot-free) samples were analyzed using different advanced statistical analysis techniques. The discrimination performance of different multivariate analysis techniques, including classification, pre-processing, and dimension reduction, were compared. Applying a random forest algorithm classifier with different pre-processing techniques to raw spectra had the best performance as the total classification accuracy of 98.7% was achieved in discriminating infected potatoes from control.

Keywords: Brown rot disease, NIR spectroscopy, potato, random forest

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Authors: Xia Chen, Hua-Quan Yang, Shi-Hua Zhou

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Alkali-active sandstone aggregate was ground by vertical and ball mill into particles with residue over 45 μm less than 12%, and investigations have been launched on particles distribution and characterization of ground sandstone powder, fluidity, heat of hydration, strength as well as hydration products morphology of pastes with incorporation of ground sandstone powder. Results indicated that ground alkali-active sandstone powder with residue over 45 μm less than 8% was easily obtainable, and specific surface area was more sensitive to characterize its fineness with extension of grinding length. Incorporation of sandstone powder resulted in higher water demand and lower strength, advanced hydration of C₃A and C₂S within 3days and refined pore structure. Based on its manufacturing, characteristics and influence on properties of pastes, it was concluded that sandstone powder was a good selection for use in concrete as mineral admixture.

Keywords: concrete, mineral admixture, hydration, structure

Procedia PDF Downloads 329

Authors: Hsiao-Yung Wang

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This essay aims to examine how the transgender imagery has been constructed in the Taiwanese news media and its evolution from 1953 to 2016. It also explores the discourse patterns and rhetorical strategies in the transgender-related issues which contributed to levels of evaluation in forming ‘social deviance.’ Samples for analysis were selected from mainstream newspapers, including China Times, United Daily and Apple Daily. The time frame for sample selection is from August 1953 (when the first transgender case was reported in Taiwan) to June 2016. To enhance understanding of media representation as nominalistic-based, the author refers to the representative of critical rhetoric Raymie McKerrow for his study on remembrance and forgetfulness in public discourse (especially in his model of ‘critique of domination’); thereby categorizing the 64 years of transgender discourse into five periods: (1) transgender as ‘intersex’ of surgical-reparative medical treatment; (2) transgender as ‘freak gender-bender’ with criminal behaviors; (3) transgender as ‘ladyboy’ (‘katoey in a Thai term) of bar girls or sex workers; (4) transgender as ‘cross dresser’ of transvestite performance; and (5) transgender as ‘life-style or human right’ of spontaneous gender identification. Based on the research findings, this essay argues that the characterization of transgender reporting as a site for the production of compulsory sexism and gender stereotype by the specific forms of name-calling. Besides, the evolution of word-image addressing to transgender issues also pinpoints media as a reflection of fashion of the day. While the transgender imagery might be crystallized as ‘still social problems’ or ‘gender transgression’ in insidious rhetoric; and while the so-called ‘phobia’ persistently embodies in media discourse to exercise name-calling in an ambiguous (rather than in a bullying) way or under the cover of humanist-liberalist rationales, these emergent rhetorical dilemma should be resolved without any delay.

Keywords: critical rhetoric, media representation, McKerrow, nominalistic, social deviance, transgender

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Authors: Gichun Cha, Byoungjoon Yu, Jihwan Park, Minsoo Park, Junghyun Im, Sehwan Park, Sujung Sin, Seunghee Park

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The goal of this research is to estimate a structural shape change using terrestrial laser scanning. This study proceeds with development of data reduction and shape change estimation algorithm for large-capacity scan data. The point cloud of scan data was converted to voxel and sampled. Technique of shape estimation is studied to detect changes in structure patterns, such as skyscrapers, bridges, and tunnels based on large point cloud data. The point cloud analysis applies the octree data structure to speed up the post-processing process for change detection. The point cloud data is the relative representative value of shape information, and it used as a model for detecting point cloud changes in a data structure. Shape estimation model is to develop a technology that can detect not only normal but also immediate structural changes in the event of disasters such as earthquakes, typhoons, and fires, thereby preventing major accidents caused by aging and disasters. The study will be expected to improve the efficiency of structural health monitoring and maintenance.

Keywords: terrestrial laser scanning, point cloud, shape information model, displacement measurement

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Authors: Y. J. Lin, Y. F. Lin

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CO2 is the primary greenhouse gas which causes global warming in recent years. As the carbon capture and storage (CCS) getting maturing, the reuse of carbon dioxide which made from CCS is the important issue. In this way, the most common method is the synthesis of cyclic carbonate chemicals from the cycloaddition reaction of carbon dioxide and epoxide. The catalyst plays an important role in the CO2/epoxide cycloaddition reactions. The Lewis acid and base sites are both needed on the catalyst surface for the help of epoxide ring opening, leading to the synthesis of cyclic carbonate. Furthermore, the larger specific surface area and more active site of the catalyst are also needed to enhance the efficiency of the CO2/epoxide cycloaddition reactions. Aerogel is a mesoporous nanomaterial (pore size between 2~50 nm) with high specific surface area and porosity (at least 90%) and low density. In this study, the ternary metal oxide aerogels, Mg-doped Al2O3 aerogels, with higher specific surface area and Lewis acid and base sites on the aerogel surface are successfully prepared by using a facile sol-gel reaction. The as-prepared Mg-doped Al2O3 aerogels are also served as heterogenous catalyst for the CO2/propylene- oxide cycloaddition reaction. Compared to the pristine Al2O3 aerogels, the Mg-doped Al2O3 aerogels possessed both Lewis acid and base sites on the surface are able to enhance the efficiency of the CO2/propylene oxide cycloaddition reactions. As a result, the as-prepared Mg-doped Al2O3 aerogels are a promising and novel catalyst for the CO2/epoxide cycloaddition reactions.

Keywords: ternary, metal oxide aerogel, CO2 reuse, cycloaddition, propylene oxide

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Authors: Mehdi Brahimi, Kamal Medjaher, Noureddine Zerhouni, Mohammed Leouatni

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The Prognostics and Health Management is a system engineering discipline which provides solutions and models to the implantation of a predictive maintenance. The approach is based on extracting useful information from monitoring data to assess the “health” state of an industrial equipment or an asset. In this paper, we examine multiple extracted features from Pantograph-Catenary contact force in order to select the most relevant ones to achieve a diagnostics function. The feature extraction methodology is based on simulation data generated thanks to a Pantograph-Catenary simulation software called INPAC and measurement data. The feature extraction method is based on both statistical and signal processing analyses. The feature selection method is based on statistical criteria.

Keywords: catenary/pantograph interaction, diagnostics, Prognostics and Health Management (PHM), quality of current collection

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Authors: Dení Stincer Gómez, Zuraya Monroy Nasr

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Pedagogy of science historically has given priority to teaching strategies that mobilize the cognitive mechanisms leaving out emotional. Modern epistemology, cognitive psychology and psychoanalysis begin to argue and prove that emotions are relevant epistemological functions. They are 1) the selection function: that allows the perception and reason choose, to multiple alternative explanation of a particular fact, those are relevant and discard those that are not, 2) heuristic function: that is related to the activation cognitive processes that are effective in the process of knowing; and 3) the function that called carrier content: on the latter it arises that emotions give the material reasoning that later transformed into linguistic propositions. According to these hypotheses, scientific knowledge seems to come from emotions that meet these functions. In this paper I argue that science education should start from the presence of certain emotions in the learner if it is to form citizens with scientific or cultural future scientists.

Keywords: epistemic emotions, science education, formation of citizens and scientists., philosophy of emotions

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Authors: Seada Hussen, Frie Ayalew

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Integrating different energy resources, like solar PV and hydro, is used to ensure reliable power to rural communities like Hara village in Ethiopia. Hybrid power system offers power supply for rural villages by providing an alternative supply for the intermittent nature of renewable energy resources. The intermittent nature of renewable energy resources is a challenge to electrifying rural communities in a sustainable manner with solar resources. Major rural villages in Ethiopia are suffering from a lack of electrification, that cause our people to suffer deforestation, travel for long distance to fetch water, and lack good services like clinic and school sufficiently. The main objective of this project is to provide a balanced, stable, reliable supply for Hara village, Ethiopia using solar power with a pumped hydro energy storage system. The design of this project starts by collecting data from villages and taking solar irradiance data from NASA. In addition to this, geographical arrangement and location are also taken into consideration. After collecting this, all data analysis and cost estimation or optimal sizing of the system and comparison of solar with pumped hydro and solar with battery storage system is done using Homer Software. And since solar power only works in the daytime and pumped hydro works at night time and also at night and morning, both load will share to cover the load demand; this need controller designed to control multiple switch and scheduling in this project fuzzy logic controller is used to control this scenario. The result of the simulation shows that solar with pumped hydro energy storage system achieves good results than with a battery storage system since the comparison is done considering storage reliability, cost, storage capacity, life span, and efficiency.

Keywords: pumped hydro storage, solar energy, solar PV, battery energy storage, fuzzy logic controller

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Authors: Babak Safaei, A. M. Fattahi

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In the present study we have investigated axial buckling characteristics of nanocomposite beams reinforced by single-walled carbon nanotubes (SWCNTs). Various types of beam theories including Euler-Bernoulli beam theory, Timoshenko beam theory and Reddy beam theory were used to analyze the buckling behavior of carbon nanotube-reinforced composite beams. Generalized differential quadrature (GDQ) method was utilized to discretize the governing differential equations along with four commonly used boundary conditions. The material properties of the nanocomposite beams were obtained using molecular dynamic (MD) simulation corresponding to both short-(10,10) SWCNT and long-(10,10) SWCNT composites which were embedded by amorphous polyethylene matrix. Then the results obtained directly from MD simulations were matched with those calculated by the mixture rule to extract appropriate values of carbon nanotube efficiency parameters accounting for the scale-dependent material properties. The selected numerical results were presented to indicate the influences of nanotube volume fractions and end supports on the critical axial buckling loads of nanocomposite beams relevant to long- and short-nanotube composites.

Keywords: nanocomposites, molecular dynamics simulation, axial buckling, generalized differential quadrature (GDQ)

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Authors: Paola Villoria Saez, Mercedes Del Rio Merino, Jaime Santacruz Astorqui, Cesar Porras Amores

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In construction the Circular Economy covers the whole cycle of the building construction: from production and consumption to waste management and the market for secondary raw materials. The circular economy will definitely contribute to 'closing the loop' of construction product lifecycles through greater recycling and re-use, helping to build a market for reused construction materials salvaged from demolition sites, boosting global competitiveness and fostering sustainable economic growth. In this context, this paper presents the latest research of 'Waste to resources (W2R)' project funded by the Spanish Government, which seeks new solutions to improve energy efficiency in buildings by developing new building materials and products that are less expensive, more durable, with higher quality and more environmentally friendly. This project differs from others as its main objective is to reduce to almost zero the Construction and Demolition Waste (CDW) generated in building rehabilitation works. In order to achieve this objective, the group is looking for new ways of CDW recycling as raw materials for new conglomerate materials. With these new materials, construction elements reducing building energy consumption will be proposed. In this paper, the results obtained in the project are presented. Several tests were performed to gypsum samples containing different percentages of CDW waste generated in Spanish building retroffiting works. Results were further analyzed and one of the gypsum composites was highlighted and discussed. Acknowledgements: This research was supported by the Spanish State Secretariat for Research, Development and Innovation of the Ministry of Economy and Competitiveness under 'Waste 2 Resources' Project (BIA2013-43061-R).

Keywords: building waste, CDW, gypsum, recycling, resources

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Authors: Sema Kayapinar, Ismail Karaoglan, Turan Paksoy, Hadi Gokcen

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Green Supply Chain Management is gaining growing interest among researchers and supply chain management. The concept of Green Supply Chain Management is to integrate environmental thinking into the Supply Chain Management. It is the systematic concept emphasis on environmental problems such as reduction of greenhouse gas emissions, energy efficiency, recycling end of life products, generation of solid and hazardous waste. This study is to present a green supply chain network model integrated Internet of Things applications. Internet of Things provides to get precise and accurate information of end-of-life product with sensors and systems devices. The forward direction consists of suppliers, plants, distributions centres and sales and collect centres while, the reverse flow includes the sales and collects centres, disassembled centre, recycling and disposal centre. The sales and collection centre sells the new products are transhipped from factory via distribution centre and also receive the end-of life product according their value level. We describe green logistics activities by presenting specific examples including “recycling of the returned products and “reduction of CO2 gas emissions”. The different transportation choices are illustrated between echelons according to their CO2 gas emissions. This problem is formulated as a mixed integer linear programming model to solve the green supply chain problems which are emerged from the environmental awareness and responsibilities. This model is solved by using Gams package program. Numerical examples are suggested to illustrate the efficiency of the proposed model.

Keywords: green supply chain optimization, internet of things, greenhouse gas emission, recycling

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Authors: Keundong Lee, Dongha Yoo, Youngbin Tchoe, Gyu-Chul Yi

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Light emitting diode (LED) array is an ideal optical stimulation tool for optogenetics, which controls inhibition and excitation of specific neurons with light-sensitive ion channels or pumps. Although a fiber-optic cable with an external light source, either a laser or LED mechanically connected to the end of the fiber-optic cable has widely been used for illumination on neural tissue, a new approach to use micro LEDs (µLEDs) has recently been demonstrated. The LEDs can be placed directly either on the cortical surface or within the deep brain using a penetrating depth probe. Accordingly, this method would not need a permanent opening in the skull if the LEDs are integrated with miniature electrical power source and wireless communication. In addition, multiple color generation from single µLED cell would enable to excite and/or inhibit neurons in localized regions. Here, we demonstrate flexible and color tunable µLEDs for the optogenetic device applications. The flexible and color tunable LEDs was fabricated using multifaceted gallium nitride (GaN) nanorod arrays with GaN nanorods grown on InxGa1−xN/GaN single quantum well structures (SQW) anisotropically formed on the nanorod tips and sidewalls. For various electroluminescence (EL) colors, current injection paths were controlled through a continuous p-GaN layer depending on the applied bias voltage. The electric current was injected through different thickness and composition, thus changing the color of light from red to blue that the LED emits. We believe that the flexible and color tunable µLEDs enable us to control activities of the neuron by emitting various colors from the single µLED cell.

Keywords: light emitting diode, optogenetics, graphene, flexible optoelectronics

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Authors: I. Nitoi, P. Oancea, M. Raileanu, M. Crisan, L. Constantin, I. Cristea

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Hazardous organic compounds like nitroaromatics are frequently found in chemical and petroleum industries discharged effluents. Due to their bio-refractory character and high chemical stability cannot be efficiently removed by classical biological or physical-chemical treatment processes. In the past decades, semiconductor photocatalysis has been frequently applied for the advanced degradation of toxic pollutants. Among various semiconductors titania was a widely studied photocatalyst, due to its chemical inertness, low cost, photostability and nontoxicity. In order to improve optical absorption and photocatalytic activity of TiO2 many attempts have been made, one feasible approach consists of doping oxide semiconductor with metal. The degradation of dinitrobenzene (DNB) and dinitrotoluene (DNT) from aqueous solution under UVA-VIS irradiation using heavy metal (0.5% Fe, 1%Co, 1%Ni ) doped titania was investigated. The photodegradation experiments were carried out using a Heraeus laboratory scale UV-VIS reactor equipped with a medium-pressure mercury lamp which emits in the range: 320-500 nm. Solutions with (0.34-3.14) x 10-4 M pollutant content were photo-oxidized in the following working conditions: pH = 5-9; photocatalyst dose = 200 mg/L; irradiation time = 30 – 240 minutes. Prior to irradiation, the photocatalyst powder was added to the samples, and solutions were bubbled with air (50 L/hour), in the dark, for 30 min. Dopant type, pH, structure and initial pollutant concentration influence on the degradation efficiency were evaluated in order to set up the optimal working conditions which assure substrate advanced degradation. The kinetics of nitroaromatics degradation and organic nitrogen mineralization was assessed and pseudo-first order rate constants were calculated. Fe doped photocatalyst with lowest metal content (0.5 wt.%) showed a considerable better behaviour in respect to pollutant degradation than Co and Ni (1wt.%) doped titania catalysts. For the same working conditions, degradation efficiency was higher for DNT than DNB in accordance with their calculated adsobance constants (Kad), taking into account that degradation process occurs on catalyst surface following a Langmuir-Hinshalwood model. The presence of methyl group in the structure of DNT allows its degradation by oxidative and reductive pathways, while DNB is converted only by reductive route, which also explain the highest DNT degradation efficiency. For highest pollutant concentration tested (3 x 10-4 M), optimum working conditions (0.5 wt.% Fe doped –TiO2 loading of 200 mg/L, pH=7 and 240 min. irradiation time) assures advanced nitroaromatics degradation (ηDNB=89%, ηDNT=94%) and organic nitrogen mineralization (ηDNB=44%, ηDNT=47%).

Keywords: hazardous organic compounds, irradiation, nitroaromatics, photocatalysis

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Authors: Simran Baweja, Bhavika Kalal, Surajit Maity

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Photoinduced tautomerization reactions have been the centre of attention among the scientific community over the past several decades because of their significance in various biological systems. 7-azaindole (7AI) is considered a model system for DNA base pairing and to understand the role of such tautomerization reactions in mutations. To the best of our knowledge, extensive studies have been carried out on 7-azaindole and its solvent clusters exhibiting proton/ hydrogen transfer in both solution as well as gas phases. Derivatives of the above molecule, like 2,7- and 2,6-diazaindoles are proposed to have even better photophysical properties due to the presence of -aza group on the 2nd position. However, there are studies in the solution phase that suggest the relevance of these molecules, but there are no experimental studies reported in the gas phase yet. In our current investigation, we present the first gas phase spectroscopic data of 2,7-diazaindole (2,7-DAI) and its solvent cluster (2,7-DAI-H2O). In this, we have employed state-of-the-art laser spectroscopic methods such as fluorescence excitation (LIF), dispersed fluorescence (DF), resonant two-photon ionization-time of flight mass spectrometry (2C-R2PI), photoionization efficiency spectroscopy (PIE), IR-UV double resonance spectroscopy, i.e., fluorescence-dip infrared spectroscopy (FDIR) and resonant ion-dip infrared spectroscopy (IDIR) to understand the electronic structure of the molecule. The origin band corresponding to the S1 ← S0 transition of the bare 2,7-DAI is found to be positioned at 33910 cm-1, whereas the origin band corresponding to S1 ← S0 transition of the 2,7-DAI-H2O is positioned at 33074 cm-1. The red-shifted transition in the case of solvent cluster suggests the enhanced feasibility of excited state hydrogen/ proton transfer. The ionization potential for the 2,7-DAI molecule is found to be 8.92 eV which is significantly higher than the previously reported 7AI (8.11 eV) molecule, making it a comparatively complex molecule to study. The ionization potential is reduced by 0.14 eV in the case of 2,7-DAI-H2O (8.78 eV) cluster compared to that of 2,7-DAI. Moreover, on comparison with the available literature values of 7AI, we found the origin band of 2,7-DAI and 2,7-DAI-H2O to be red-shifted by -729 and -280 cm-1 respectively. The ground and excited state N-H stretching frequencies of the 27DAI molecule were determined using fluorescence-dip infrared spectra (FDIR) and resonant ion dip infrared spectroscopy (IDIR), obtained at 3523 and 3467 cm-1, respectively. The lower value of vNH in the electronically excited state of 27DAI implies the higher acidity of the group compared to the ground state. Moreover, we have done extensive computational analysis, which suggests that the energy barrier in the excited state reduces significantly as we increase the number of catalytic solvent molecules (S= H2O, NH3) as well as the polarity of solvent molecules. We found that the ammonia molecule is a better candidate for hydrogen transfer compared to water because of its higher gas-phase basicity. Further studies are underway to understand the excited state dynamics and photochemistry of such N-rich chromophores.

Keywords: excited state hydrogen transfer, supersonic expansion, gas phase spectroscopy, IR-UV double resonance spectroscopy, laser induced fluorescence, photoionization efficiency spectroscopy

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Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

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The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

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Authors: Chantouch Wannathanom

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Research The study of elders’ needs in Bangkok metropolis for the options of health tourism. The objective is to study of elders’ needs in Bangkok Metropolis for the options of health tourism. The research her collected data using a questionnaire. The samples used in this research is elderly people living in the Dusit area. Of 400 people found the majority were female than male. Accounted for18 percent aged between 50-55 years, mostly undergraduate degree. Moreover, most seniors do not have underlying disease. The study found that 1. Elders’ needs in Bangkok Metropolis for the options of health tourism; 2. Tourism activity patterns that fit elderly was divided into 5 categories, including massage, massage, and herbal sauna. Practicing meditation and ascetic. The results showed that selection of elderly tourist activities by choosing healthy eating are the first. The hypothesis testing period: Elders’ needs in Bangkok Metropolis for the options of health tourism is different. The level of statistical significance .05 level.

Keywords: needs, elder, health tourism, Bangkok

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Authors: Ángel de J. López-Pérez, Sonia E. Ruiz, Vanessa A. Segovia

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Buildings vulnerability due to seismic activity has been highly studied since the middle of last century. As a solution to the structural and non-structural damage caused by intense ground motions, several seismic energy dissipating devices, such as buckling-restrained braces (BRB), have been proposed. BRB have shown to be effective in concentrating a large portion of the energy transmitted to the structure by the seismic ground motion. A design approach for buildings with BRB elements, which is based on a seismic Displacement-Based formulation, has recently been proposed by the coauthors in this paper. It is a practical and easy design method which simplifies the work of structural engineers. The method is used here for the design of the structure-BRB damper system. The objective of the present study is to extend and apply a methodology to find the best combination of design parameters on multiple-degree-of-freedom (MDOF) structural frame – BRB systems, taking into account simultaneously: 1) initial costs and 2) an adequate engineering demand parameter. The design parameters considered here are: the stiffness ratio (α = K_frame/K_total), and the strength ratio (γ = V_damper/V_total); where K represents structural stiffness and V structural strength; and the subscripts "frame", "damper" and "total" represent: the structure without dampers, the BRB dampers and the total frame-damper system, respectively. The selection of the best combination of design parameters α and γ is based on an initial costs analysis and on the structural dynamic response of the structural frame-damper system. The methodology is applied to a 12-story 5-bay steel building with BRB, which is located on the intermediate soil of Mexico City. It is found the best combination of design parameters α and γ for the building with BRB under study.

Keywords: best combination of design parameters, BRB, buildings with energy dissipating devices, buckling-restrained braces, initial costs

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Authors: Georgi Y. Georgiev, Matthew Brouillet

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This research applies the power of agent-based modeling to a pivotal question at the intersection of biology, computer science, physics, and complex systems theory about the self-organization processes in open, complex, non-equilibrium thermodynamic systems. Central to this investigation is the principle of Maximum Entropy Production (MEP). This principle suggests that such systems evolve toward states that optimize entropy production, leading to the formation of structured environments. It is hypothesized that guided by the least action principle, open thermodynamic systems identify and follow the shortest paths to transmit energy and matter, resulting in maximal entropy production, internal structure formation, and a decrease in internal entropy. Concurrently, it is predicted that there will be an increase in system information as more information is required to describe the developing structure. To test this, an agent-based model is developed simulating an ant colony's formation of a path between a food source and its nest. Utilizing the Netlogo software for modeling and Python for data analysis and visualization, self-organization is quantified by calculating the decrease in system entropy based on the potential states and distribution of the ants within the simulated environment. External entropy production is also evaluated for information increase and efficiency improvements in the system's action. Simulations demonstrated that the system begins at maximal entropy, which decreases as the ants form paths over time. A range of system behaviors contingent upon the number of ants are observed. Notably, no path formation occurred with fewer than five ants, whereas clear paths were established by 200 ants, and saturation of path formation and entropy state was reached at populations exceeding 1000 ants. This analytical approach identified the inflection point marking the transition from disorder to order and computed the slope at this point. Combined with extrapolation to the final path entropy, these parameters yield important insights into the eventual entropy state of the system and the timeframe for its establishment, enabling the estimation of the self-organization rate. This study provides a novel perspective on the exploration of self-organization in thermodynamic systems, establishing a correlation between internal entropy decrease rate and external entropy production rate. Moreover, it presents a flexible framework for assessing the impact of external factors like changes in world size, path obstacles, and friction. Overall, this research offers a robust, replicable model for studying self-organization processes in any open thermodynamic system. As such, it provides a foundation for further in-depth exploration of the complex behaviors of these systems and contributes to the development of more efficient self-organizing systems across various scientific fields.

Keywords: complexity, self-organization, agent based modelling, efficiency

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Authors: Stefan K. Behfar

Abstract:

The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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