Search results for: circuit models

Authors: Tolulope Aremu

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The key process steps to produce liquid detergent products will introduce potential defects, such as formulation, mixing, filling, and packaging, which might compromise product quality, consumer safety, and operational efficiency. Real-time identification and characterization of such defects are of prime importance for maintaining high standards and reducing waste and costs. Usually, defect detection is performed by human inspection or rule-based systems, which is very time-consuming, inconsistent, and error-prone. The present study overcomes these limitations in dealing with optimization in defect characterization within the process for making liquid detergents using Machine Learning algorithms. Performance testing of various machine learning models was carried out: Support Vector Machine, Decision Trees, Random Forest, and Convolutional Neural Network on defect detection and classification of those defects like wrong viscosity, color deviations, improper filling of a bottle, packaging anomalies. These algorithms have significantly benefited from a variety of optimization techniques, including hyperparameter tuning and ensemble learning, in order to greatly improve detection accuracy while minimizing false positives. Equipped with a rich dataset of defect types and production parameters consisting of more than 100,000 samples, our study further includes information from real-time sensor data, imaging technologies, and historic production records. The results are that optimized machine learning models significantly improve defect detection compared to traditional methods. Take, for instance, the CNNs, which run at 98% and 96% accuracy in detecting packaging anomaly detection and bottle filling inconsistency, respectively, by fine-tuning the model with real-time imaging data, through which there was a reduction in false positives of about 30%. The optimized SVM model on detecting formulation defects gave 94% in viscosity variation detection and color variation. These values of performance metrics correspond to a giant leap in defect detection accuracy compared to the usual 80% level achieved up to now by rule-based systems. Moreover, this optimization with models can hasten defect characterization, allowing for detection time to be below 15 seconds from an average of 3 minutes using manual inspections with real-time processing of data. With this, the reduction in time will be combined with a 25% reduction in production downtime because of proactive defect identification, which can save millions annually in recall and rework costs. Integrating real-time machine learning-driven monitoring drives predictive maintenance and corrective measures for a 20% improvement in overall production efficiency. Therefore, the optimization of machine learning algorithms in defect characterization optimum scalability and efficiency for liquid detergent companies gives improved operational performance to higher levels of product quality. In general, this method could be conducted in several industries within the Fast moving consumer Goods industry, which would lead to an improved quality control process.

Keywords: liquid detergent manufacturing, defect detection, machine learning, support vector machines, convolutional neural networks, defect characterization, predictive maintenance, quality control, fast-moving consumer goods

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Authors: Jeffrey Tzu-Hao Tsai, Yi-Shan Wong

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This article proposes a cohort-age-period (CAP) model to characterize multi-population mortality processes using cohort, age, and period variables. Distinct from the factor-based Lee-Carter-type decomposition mortality model, this approach is empirically based and includes the age, period, and cohort variables into the equation system. The model not only provides a fruitful intuition for explaining multivariate mortality change rates but also has a better performance in forecasting future patterns. Using the US and the UK mortality data and performing ten-year out-of-sample tests, our approach shows smaller mean square errors in both countries compared to the models in the literature.

Keywords: longevity risk, stochastic mortality model, multivariate mortality rate, risk management

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Authors: Serpil Türkyılmaz, Mesut Balıbey

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In this study, long memory properties in volatility of Turkey Stock Market are being examined through the FIGARCH, FIEGARCH and FIAPARCH models under different distribution assumptions as normal and skewed student-t distributions. Furthermore, structural changes in volatility of Turkey Stock Market are investigated. The results display long memory property and the presence of asymmetric effects of shocks in volatility of Turkey Stock Market.

Keywords: FIAPARCH model, FIEGARCH model, FIGARCH model, structural break

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Authors: T. Watanabe

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Combustion analysis of suspended sodium droplet is performed by solving numerically the Navier-Stokes equations and the energy conservation equations. The combustion model consists of the pre-ignition and post-ignition models. The reaction rate for the pre-ignition model is based on the chemical kinetics, while that for the post-ignition model is based on the mass transfer rate of oxygen. The calculated droplet temperature is shown to be in good agreement with the existing experimental data. The temperature field in and around the droplet is obtained as well as the droplet shape variation, and the present numerical model is confirmed to be effective for the combustion analysis.

Keywords: analysis, combustion, droplet, sodium

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Authors: T. N. Mac, B. Shahbodaghkhan, N. Khalili

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A new elastic-viscoplastic (EVP) constitutive model is proposed for the analysis of time-dependent behavior of clay. The proposed model is based on the bounding surface plasticity and the concept of viscoplastic consistency framework to establish continuous transition from plasticity to rate dependent viscoplasticity. Unlike the overstress based models, this model will meet the consistency condition in formulating the constitutive equation for EVP model. The procedure of deriving the constitutive relationship is also presented. Simulation results and comparisons with experimental data are then presented to demonstrate the performance of the model.

Keywords: bounding surface, consistency theory, constitutive model, viscosity

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Authors: Henrique Rangel, Alexandre Fadel, Igor De Lazari, Bianca Neri, Carlos Bolonha

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This paper promotes a comparative analysis of American and Brazilian models of federalism assuming their levels of political centralization as main criterion. The central problem faced herein is the Brazilian approach of Unitarian regime. Although the hegemony of federative form after 1989, Brazil had a historical frame of political centralization that remains under the 1988 constitutional regime. Meanwhile, United States framed a federalism in which States absorb significant authorities. The hypothesis holds that the amount of alternative criteria of federalization – which can generate political centralization –, and the way they are upheld on judicial review, are crucial to understand the levels of political centralization achieved in each model. To test this hypothesis, the research is conducted by a methodology temporally delimited to 1994-2014 period. Three paradigmatic precedents of U.S. Supreme Court were selected: United States vs. Morrison (2000), on gender-motivated violence, Gonzales vs. Raich (2005), on medical use of marijuana, and United States vs. Lopez (1995), on firearm possession on scholar zones. These most relevant cases over federalism in the recent activity of Supreme Court indicates a determinant parameter of deliberation: the commerce clause. After observe the criterion used to permit or prohibit the political centralization in America, the Brazilian normative context is presented. In this sense, it is possible to identify the eventual legal treatment these controversies could receive in this Country. The decision-making reveals some deliberative parameters, which characterizes each federative model. At the end of research, the precedents of Rehnquist Court promote a broad revival of federalism debate, establishing the commerce clause as a secure criterion to uphold or not the necessity of centralization – even with decisions considered conservative. Otherwise, the Brazilian federalism solves them controversies upon in a formalist fashion, within numerous and comprehensive – sometimes casuistic too – normative devices, oriented to make an intense centralization. The aim of this work is indicate how jurisdictional federalism found in United States can preserve a consistent model with States robustly autonomous, while Brazil gives preference to normative mechanisms designed to starts from centralization.

Keywords: constitutional design, federalism, U.S. Supreme Court, legislative authority

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Authors: K. P. Mredula, D. C. Vakaskar

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The article traces developments and evolution of various algorithms developed for solving partial differential equations using the significant combination of wavelet with few already explored solution procedures. The approach depicts a study over a decade of traces and remarks on the modifications in implementing multi-resolution of wavelet, finite difference approach, finite element method and finite volume in dealing with a variety of partial differential equations in the areas like plasma physics, astrophysics, shallow water models, modified Burger equations used in optical fibers, biology, fluid dynamics, chemical kinetics etc.

Keywords: multi-resolution, Haar Wavelet, partial differential equation, numerical methods

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Authors: Amr Mohamadien, Ali Imanpour, Sylvester Agbo, Nader Yoosef-Ghodsi, Samer Adeeb

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The fracture toughness resistance curve (e.g., J-R curve and crack tip opening displacement (CTOD) or δ-R curve) is important in facilitating strain-based design and integrity assessment of oil and gas pipelines. This paper aims to present laboratory experimental data to characterize the fracture behavior of pipeline steel. The influential parameters associated with the fracture of API 5L X52 pipeline steel, including different initial crack sizes, were experimentally investigated for a single notch edge bend (SENB). A total of 9 small-scale specimens with different crack length to specimen depth ratios were conducted and tested using single edge notch bending (SENB). ASTM E1820 and BS7448 provide testing procedures to construct the fracture resistance curve (Load-CTOD, CTOD-R, or J-R) from test results. However, these procedures are limited by standard specimens’ dimensions, displacement gauges, and calibration curves. To overcome these limitations, this paper presents the use of small-scale specimens and a 3D-digital image correlation (DIC) system to extract the parameters required for fracture toughness estimation. Fracture resistance curve parameters in terms of crack mouth open displacement (CMOD), crack tip opening displacement (CTOD), and crack growth length (∆a) were carried out from test results by utilizing the DIC system, and an improved regression fitting resistance function (CTOD Vs. crack growth), or (J-integral Vs. crack growth) that is dependent on a variety of initial crack sizes was constructed and presented. The obtained results were compared to the available results of the classical physical measurement techniques, and acceptable matchings were observed. Moreover, a case study was implemented to estimate the maximum strain value that initiates the stable crack growth. This might be of interest to developing more accurate strain-based damage models. The results of laboratory testing in this study offer a valuable database to develop and validate damage models that are able to predict crack propagation of pipeline steel, accounting for the influential parameters associated with fracture toughness.

Keywords: fracture toughness, crack propagation in pipeline steels, CTOD-R, strain-based damage model

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Authors: Vicente Espinola, Luis Torres, Christhian Gonzalez

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Entrepreneurship is a topic of current interest in Mexico and the World, which has been fostered through public policies with great impact on its generation. The strategies used in Mexico have not been successful, being motivational strategies aimed at the masses with the intention that someone in the process generates a venture. The strategies used for its development have been "picking of winners" favoring those who have already overcome the initial stages of undertaking without effective support. This situation shows a disarticulation that appears even more in social entrepreneurship; due to this, it is relevant to research on those elements that could develop them and thus integrate a model of entrepreneurship and social innovation for Mexico. Social entrepreneurship should be generating social innovation, which is translated into business models in order to make the benefits reach the population. These models are proposed putting the social impact before the economic impact, without forgetting its sustainability in the medium and long term. In this work, we present a simple model of innovation and social entrepreneurship for Guanajuato, Mexico. This algorithm was based on how social innovation could be generated in a systemic way for Mexico through different institutions that promote innovation. In this case, the technological parks of the state of Guanajuato were studied because these are considered one of the areas of Mexico where its main objectives are to make technology transfer to companies but overlooking the social sector and entrepreneurs. An experimental design of n = 60 was carried out with potential entrepreneurs to identify their perception of the social approach that the enterprises should have, the skills they consider required to create a venture, as well as their interest in generating ventures that solve social problems. This experiment had a 2K design, the value of k = 3 and the computational simulation was performed in R statistical language. A simple model of interconnected variables is proposed, which allows us to identify where it is necessary to increase efforts for the generation of social enterprises. The 96.67% of potential entrepreneurs expressed interest in ventures that solve social problems. In the analysis of the variables interaction, it was identified that the isolated development of entrepreneurial skills would only replicate the generation of traditional ventures. The variable of social approach presented positive interactions, which may influence the generation of social entrepreneurship if this variable was strengthened and permeated in the processes of training and development of entrepreneurs. In the future, it will be necessary to analyze the institutional actors that are present in the social entrepreneurship ecosystem, in order to analyze the interaction necessary to strengt the innovation and social entrepreneurship ecosystem.

Keywords: social innovation, model, entrepreneurship, technological parks

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Authors: Olfa Kaabia, Ilyes Abid, Khaled Guesmi

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This pioneer paper studies whether and how Bitcoin shocks are transmitted to the U.S economy. We employ a new methodology: TVP FAVAR model with stochastic volatility. We use a large dataset of 111 major U.S variables from 1959:m1 to 2016:m12. The results show that Bitcoin shocks significantly impact the U.S. economy. This significant impact is pronounced in a volatile and increasing U.S economy. The Bitcoin has a positive relationship on the U.S real activity, and a negative one on U.S prices and interest rates. Effects on the Monetary Policy exist via the inter-est rates and the Money, Credit and Finance transmission channels.

Keywords: bitcoin, US economy, FAVAR models, stochastic volatility

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Authors: Elyes Zarrouk, Yassine Benayed, Faiez Gargouri

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This paper presents a new hybrid model for isolated Arabic words recognition. To do this, we apply Support Vectors Machine (SVM) as an estimator of posterior probabilities within the Dynamic Bayesian networks (DBN). This paper deals a comparative study between DBN and SVM/DBN systems for multi-dialect isolated Arabic words. Performance using SVM/DBN is found to exceed that of DBNs trained on an identical task, giving higher recognition accuracy for four different Arabic dialects. In fact, the average of recognition rates for the four dialects with SVM/DBN was 87.67% while 83.01% with DBN.

Keywords: dynamic Bayesian networks, hybrid models, supports vectors machine, Arabic isolated words

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Authors: Wilhelmina van den Berg

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Through intentionally developing the Register Continuum and the Functional Model of Language in the secondary history classroom, teachers can effectively build a teaching and learning cycle geared towards literacy improvement and EAL differentiation. Developing an understanding of and engaging students in the field, tenor, and tone of written and spoken language, allows students to build the foundation for greater academic achievement due to integrated literacy skills in the history classroom. Building a variety of scaffolds during lessons within these models means students can improve their academic language and communication skills.

Keywords: academic language, EAL, functional model of language, international baccalaureate, literacy skills

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Authors: Masoomeh Alsadat Mirshafaei

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The present study aims to explore the effect of an 8-week aerobic training regimen combined with cinnamon extract on serum irisin and leptin levels in insulin-resistant rats. Additionally, this research leverages various machine learning (ML) and deep learning (DL) algorithms to model the complex interdependencies between exercise, nutrition, and metabolic markers, offering a groundbreaking approach to obesity and diabetes research. Forty-eight Wistar rats were selected and randomly divided into four groups: control, training, cinnamon, and training cinnamon. The training protocol was conducted over 8 weeks, with sessions 5 days a week at 75-80% VO2 max. The cinnamon and training-cinnamon groups were injected with 200 ml/kg/day of cinnamon extract. Data analysis included serum data, dietary intake, exercise intensity, and metabolic response variables, with blood samples collected 72 hours after the final training session. The dataset was analyzed using one-way ANOVA (P<0.05) and fed into various ML and DL models, including Support Vector Machines (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN). Traditional statistical methods indicated that aerobic training, with and without cinnamon extract, significantly increased serum irisin and decreased leptin levels. Among the algorithms, the CNN model provided superior performance in identifying specific interactions between cinnamon extract concentration and exercise intensity, optimizing the increase in irisin and the decrease in leptin. The CNN model achieved an accuracy of 92%, outperforming the SVM (85%) and RF (88%) models in predicting the optimal conditions for metabolic marker improvements. The study demonstrated that advanced ML and DL techniques could uncover nuanced relationships and potential cellular responses to exercise and dietary supplements, which is not evident through traditional methods. These findings advocate for the integration of advanced analytical techniques in nutritional science and exercise physiology, paving the way for personalized health interventions in managing obesity and diabetes.

Keywords: aerobic training, cinnamon extract, insulin resistance, irisin, leptin, convolutional neural networks, exercise physiology, support vector machines, random forest

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Authors: Saulius Minkevicius, Edvinas Greicius

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The paper is devoted to the analysis of queueing systems in the context of the network and communications theory. We investigate the inequality in an open queueing network and its applications to the theorems in heavy traffic conditions (fluid approximation, functional limit theorem, and law of the iterated logarithm) for a queue of customers in an open queueing network.

Keywords: fluid approximation, heavy traffic, models of information systems, open queueing network, queue length of customers, queueing theory

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Authors: Pauline E. Ngo-Henha

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Existing turnover intention theories are reviewed in this paper. This review was conducted with the help of the search keyword “turnover intention theories” in Google Scholar during the month of July 2017. These theories include: The Theory of Organizational Equilibrium (TOE), Social Exchange Theory, Job Embeddedness Theory, Herzberg’s Two-Factor Theory, the Resource-Based View, Equity Theory, Human Capital Theory, and the Expectancy Theory. One of the limitations of this review paper is that data were only collected from Google Scholar where many papers were sometimes not freely accessible. However, this paper attempts to contribute to the research in clarifying the distinction between theories and models in the context of turnover intention.

Keywords: Literature Review, Theory, Turnover, Turnover intention

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Authors: Chandranath Chatterjee, Amina Khatun, Bhabagrahi Sahoo

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With the changing climate, precipitation events are intensified in the tropical river basins. Since these river basins are significantly influenced by the monsoonal rainfall pattern, critical impacts are observed on the agricultural practices in the downstream river reaches. This study analyses the crop damage and associated flood risk in terms of net benefit in the paddy-dominated tropical Indian delta of the Mahanadi River. The Mahanadi River basin lies in eastern part of the Indian sub-continent and is greatly affected by the southwest monsoon rainfall extending from the month of June to September. This river delta is highly flood-prone and has suffered from recurring high floods, especially after the 2000s. In this study, the lumped conceptual model, Nedbør Afstrømnings Model (NAM) from the suite of MIKE models, is used for rainfall-runoff modeling. The NAM model is laterally integrated with the MIKE11-Hydrodynamic (HD) model to route the runoffs up to the head of the delta region. To obtain the precipitation-derived future projected discharges at the head of the delta, nine Global Climate Models (GCMs), namely, BCC-CSM1.1(m), GFDL-CM3, GFDL-ESM2G, HadGEM2-AO, IPSL-CM5A-LR, IPSL-CM5A-MR, MIROC5, MIROC-ESM-CHEM and NorESM1-M, available in the Coupled Model Intercomparison Project-Phase 5 (CMIP5) archive are considered. These nine GCMs are previously found to best-capture the Indian Summer Monsoon rainfall. Based on the performance of the nine GCMs in reproducing the historical discharge pattern, three GCMs (HadGEM2-AO, IPSL-CM5A-MR and MIROC-ESM-CHEM) are selected. A higher Taylor Skill Score is considered as the GCM selection criteria. Thereafter, the 10-year return period design flood is estimated using L-moments based flood frequency analysis for the historical and three future projected periods (2010-2039, 2040-2069 and 2070-2099) under Representative Concentration Pathways (RCP) 4.5 and 8.5. A non-dimensional hydrograph analysis is performed to obtain the hydrographs for the historical/projected 10-year return period design floods. These hydrographs are forced into the calibrated and validated coupled 1D-2D hydrodynamic model, MIKE FLOOD, to simulate the flood inundation in the delta region. Historical and projected flood risk is defined based on the information about the flood inundation simulated by the MIKE FLOOD model and the inundation depth-damage-duration relationship of a normal rice variety cultivated in the river delta. In general, flood risk is expected to increase in all the future projected time periods as compared to the historical episode. Further, in comparison to the 2010s (2010-2039), an increased flood risk in the 2040s (2040-2069) is shown by all the three selected GCMs. However, the flood risk then declines in the 2070s as we move towards the end of the century (2070-2099). The methodology adopted herein for flood risk assessment is one of its kind and may be implemented in any world-river basin. The results obtained from this study can help in future flood preparedness by implementing suitable flood adaptation strategies.

Keywords: flood frequency analysis, flood risk, global climate models (GCMs), paddy cultivation

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Authors: Klazina T. Havinga, Hilde R. H. de Geus

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Introduction: Pre-operative coagulation management of Apixaban prescribed patients, a new oral anticoagulant (a factor Xa inhibitor), is difficult, especially when chronic kidney disease (CKD) causes drug overdose. Apixaban is not dialyzable due to its high level of protein binding. An antidote, Andexanet α, is available but expensive and has an unfavorable short half-life. We report the successful extracorporeal removal of Apixaban prior to emergency surgery with the CytoSorb® Hemoadsorption device. Methods: A 89-year-old woman with CKD, with an Apixaban prescription for atrial fibrillation, was presented at the ER with traumatic rib fractures, a flail chest, and an unstable spinal fracture (T12) for which emergency surgery was indicated. However, due to very high Apixaban levels, this surgery had to be postponed. Based on the Apixaban-specific anti-factor Xa activity (AFXaA) measurements at admission and 10 hours later, complete clearance was expected after 48 hours. In order to enhance the Apixaban removal and reduce the time to operation, and therefore reduce pulmonary complications, CRRT with CytoSorb® cartridge was initiated. Apixaban-specific anti-factor Xa activity (AFXaA) was measured frequently as a substitute for Apixaban drug concentrations, pre- and post adsorber, in order to calculate the adsorber-related clearance. Results: The admission AFXaA concentration, as a substitute for Apixaban drug levels, was 218 ng/ml, which decreased to 157 ng/ml after ten hours. Due to sustained anticoagulation effects, surgery was again postponed. However, the AFXaA levels decreased quickly to sub-therapeutic levels after CRRT (Multifiltrate Pro, Fresenius Medical Care, Blood flow 200 ml/min, Dialysate Flow 4000 ml/h, Prescribed renal dose 51 ml-kg-h) with Cytosorb® connected in series into the circuit was initiated (within 5 hours). The adsorber-related (indirect) Apixaban clearance was calculated every half hour (Cl=Qe * (AFXaA pre- AFXaA post/ AFXaA pre) with Qe=plasma flow rate calculated with Ht=0.38 and system blood flow rate 200 ml-min): 100 ml/min, 72 ml/min and 57 ml/min. Although, as expected, the adsorber-related clearance decreased quickly due to saturation of the beads, still the reduction rate achieved resulted in a very rapid decrease in AFXaA levels. Surgery was ordered and possible within 5 hours after Cytosorb initiation. Conclusion: The CytoSorb® Hemoadsorption device enabled rapid correction of Apixaban associated anticoagulation.

Keywords: Apixaban, CytoSorb, emergency surgery, Hemoadsorption

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Authors: Su-Lien Liao

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Most of college students in Taiwan do not have sufficient English proficiency to express themselves in written English. Teachers spent a lot of time correcting students’ English writing, but the results are not satisfactory. This study aims to use blogs as a teaching and learning tool in written English. Before applying peer assessment, students should be trained to be good reviewers. The teacher starts the course by posting the error analysis of students’ first English composition on blogs as the comment models for students. Then the students will go through the process of drafting, composing, peer response and last revision on blogs. Evaluation Questionnaires and interviews will be conducted at the end of the course to see the impact and students’ perception for the course.

Keywords: blog, peer assessment, English writing, error analysis

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Authors: Diqin Qi, Jiaming Li, Siman Li

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Based on the use of the three-point smoothing method for selectively processing original data columns, this paper establishes a group of grey GM(1,1) models to predict the concentration ranges of four major air pollutants in Shanghai from 2023 to 2024. The results indicate that PM₁₀, SO₂, and NO₂ maintain the national Grade I standards, while the concentration of PM₂.₅ has decreased but still remains within the national Grade II standards. Combining the forecast results, recommendations are provided for the Shanghai municipal government's efforts in air pollution prevention and control.

Keywords: atmospheric pollutant prediction, Grey GM(1, 1), model group, three-point smoothing method

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Authors: G. Henini, Y. Laidani, F. Souahi, A. Labbaci, S. Hanini

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Environmental contamination is a major problem being faced by the society today. Industrial, agricultural, and domestic wastes, due to the rapid development in the technology, are discharged in the several receivers. Generally, this discharge is directed to the nearest water sources such as rivers, lakes, and seas. While the rates of development and waste production are not likely to diminish, efforts to control and dispose of wastes are appropriately rising. Wastewaters from textile industries represent a serious problem all over the world. They contain different types of synthetic dyes which are known to be a major source of environmental pollution in terms of both the volume of dye discharged and the effluent composition. From an environmental point of view, the removal of synthetic dyes is of great concern. Among several chemical and physical methods, adsorption is a promising technique due to the ease of use and low cost compared to other applications in the process of discoloration, especially if the adsorbent is inexpensive and readily available. The focus of the present study was to assess the potentiality of Brahea edulis (BE) for the removal of synthetic dye Yellow bemacid (YB) from aqueous solutions. The results obtained here may transfer to other dyes with a similar chemical structure. Biosorption studies were carried out under various parameters such as mass adsorbent particle, pH, contact time, initial dye concentration, and temperature. The biosorption kinetic data of the material (BE) was tested by the pseudo first-order and the pseudo-second-order kinetic models. Thermodynamic parameters including the Gibbs free energy ΔG, enthalpy ΔH, and entropy ΔS have revealed that the adsorption of YB on the BE is feasible, spontaneous, and endothermic. The equilibrium data were analyzed by using Langmuir, Freundlich, Elovich, and Temkin isotherm models. The experimental results show that the percentage of biosorption increases with an increase in the biosorbent mass (0.25 g: 12 mg/g; 1.5 g: 47.44 mg/g). The maximum biosorption occurred at around pH value of 2 for the YB. The equilibrium uptake was increased with an increase in the initial dye concentration in solution (C_o = 120 mg/l; q = 35.97 mg/g). Biosorption kinetic data were properly fitted with the pseudo-second-order kinetic model. The best fit was obtained by the Langmuir model with high correlation coefficient (R² > 0.998) and a maximum monolayer adsorption capacity of 35.97 mg/g for YB.

Keywords: adsorption, Brahea edulis, isotherm, yellow Bemacid

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Authors: Marianna Bolla

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The aim of this paper is to compare spectral, discrepancy, and degree properties of expanding graph sequences. As we can prove equivalences and implications between them and the definition of the generalized (multiclass) quasirandomness of Lovasz–Sos (2008), they can be regarded as generalized quasirandom properties akin to the equivalent quasirandom properties of the seminal Chung-Graham-Wilson paper (1989) in the one-class scenario. Since these properties are valid for deterministic graph sequences, irrespective of stochastic models, the partial implications also justify for low-dimensional embedding of large-scale graphs and for discrepancy minimizing spectral clustering.

Keywords: generalized random graphs, multiway discrepancy, normalized modularity spectra, spectral clustering

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Authors: Ephraim Daka, Maxim Kotsemir

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The National system Innovation (NSI) have recently proliferated as a vehicle for addressing poverty and national competitiveness in the developing countries. While several governments in Sub-Saharan Africa have adopted the developed countries’ models of innovation to local conditions, the Zambian case is rather unique. This study highlights conceptual and socioeconomic challenges directed to the performances of the NSI. The paper analyses science and technology strategies with the inclusion of “innovation” and its effect towards improving socioeconomic elements. The authors reviewed STI policy and national strategy documents, followed by interviews compared to economical regional and national data sets. The NSI and its related to inter-linkages and support mechanism to socioeconomic development were explored.

Keywords: national system of innovation, socioeconomics, development, Zambia

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Authors: Krisztina Szegedi, Gyula Fülöp, Ádám Bereczk

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The shared goal of social entrepreneurship, corporate social responsibility and social innovation is the advancement of society. The business model of social enterprises is characterized by unique strategies based on the competencies of the entrepreneurs, and is not aimed primarily at the maximization of profits, but rather at carrying out goals for the benefit of society. Corporate social responsibility refers to the active behavior of a company, by which it can create new solutions to meet the needs of society, either on its own or in cooperation with other social stakeholders. The objectives of this article are to define concepts, describe and integrate relevant theoretical models, develop a model and introduce some examples of international practice that can inspire initiatives for social development.

Keywords: corporate social responsibility, CSR, social innovation, social entrepreneurship

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Authors: Ässia Boukhatmi, Roger Nyffenegger

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The expansion of solar energy as a means to address the climate crisis is undisputed, but the increasing number of new photovoltaic (PV) modules being put on the market is simultaneously leading to increased challenges in terms of managing the growing waste stream. Many of the discarded modules are still fully functional but are often damaged by improper handling after disassembly or not properly tested to be considered for a second life. In addition, the collection rate for dismantled PV modules in several European countries is only a fraction of previous projections, partly due to the increased number of illegal exports. The underlying problem for those market imperfections is an insufficient data exchange between the different actors along the PV value chain, as well as the limited traceability of PV panels during their lifetime. As part of the Horizon 2020 project CIRCUSOL, an asset database prototype was developed to tackle the described problems. In an iterative process applying the design science research methodology, different business models, as well as the technical implementation of the database, were established and evaluated. To explore the requirements of different stakeholders for the development of the database, surveys and in-depth interviews were conducted with various representatives of the solar industry. The proposed database prototype maps the entire value chain of PV modules, beginning with the digital product passport, which provides information about materials and components contained in every module. Product-related information can then be expanded with performance data of existing installations. This information forms the basis for the application of data analysis methods to forecast the appropriate end-of-life strategy, as well as the circular economy potential of PV modules, already before they arrive at the recycling facility. The database prototype could already be enriched with data from different data sources along the value chain. From a business model perspective, the database offers opportunities both in the area of reuse as well as with regard to the certification of sustainable modules. Here, participating actors have the opportunity to differentiate their business and exploit new revenue streams. Future research can apply this approach to further industry and product sectors, validate the database prototype in a practical context, and can serve as a basis for standardization efforts to strengthen the circular economy.

Keywords: business model, circular economy, database, design science research, solar industry

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Authors: Chabungbam Niranjit Khuman, Makarand Madhao Ghangrekar, Arunabha Mitra

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The cost of aeration is one of the limiting factors in the upscaling of microbial fuel cells (MFC) for field-scale applications. Wetland macrophytes have the ability to release oxygen into the water to maintain aerobic conditions in their root zone. In this experiment, the efficacy of rhizospheric oxygen release of wetland macrophytes as a source of oxygen in the cathodic chamber of MFC was conducted. The experiment was conducted in an MFC consisting of a three-liter anodic chamber made of ceramic cylinder and a 27 L cathodic chamber. Untreated carbon felts were used as electrodes (i.e., anode and cathode) and connected to an external load of 100 Ω using stainless steel wire. Wetland macrophytes (Canna indica) were grown in the cathodic chamber of the MFC in a hydroponic fashion using a styrofoam sheet (termed as macrophytes assisted-microbial fuel cell, M-MFC). The catholyte (i.e., water) in the M-MFC had negligible contact with atmospheric air due to the styrofoam sheet used for maintaining the hydroponic condition. There was no mixing of the catholyte in the M-MFC. Sucrose based synthetic wastewater having chemical oxygen demand (COD) of 3000 mg/L was fed into the anodic chamber of the MFC in fed-batch mode with a liquid retention time of four days. The C. indica thrived well throughout the duration of the experiment without much care. The average dissolved oxygen (DO) concentration and pH value in the M-MFC were 3.25 mg/L and 7.07, respectively, in the catholyte. Since the catholyte was not in contact with air, the DO in the catholyte might be considered as solely liberated from the rhizospheric oxygen release of C. indica. The maximum COD removal efficiency of M-MFC observed during the experiment was 76.9%. The inadequacy of terminal electron acceptor in the cathodic chamber in M-MFC might have hampered the electron transfer, which in turn, led to slower specific microbial activity, thereby resulting in lower COD removal efficiency than the traditional MFC with aerated catholyte. The average operating voltage (OV) and open-circuit voltage (OCV) of 294 mV and 594 mV, respectively, were observed in M-MFC. The maximum power density observed during polarization was 381 mW/m³, and the maximum sustainable power density observed during the experiment was 397 mW/m³ in M-MFC. The maximum normalized energy recovery and coulombic efficiency of 38.09 Wh/m³ and 1.27%, respectively, were observed. Therefore, it was evidenced that rhizospheric oxygen release of wetland macrophytes (C. indica) was capable of sustaining the cathodic reaction in MFC for field-scale applications.

Keywords: hydroponic, microbial fuel cell, rhizospheric oxygen release, wetland macrophytes

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Authors: Yi-Cheng Tian, Miin-Shen Yang

Abstract:

The mixture likelihood approach to clustering is a popular clustering method where the expectation and maximization (EM) algorithm is the most used mixture likelihood method. In the literature, the EM algorithm had been used for mixture regression models. However, these EM mixture regression algorithms are sensitive to initial values with a priori number of clusters. In this paper, to resolve these drawbacks, we construct a learning-based schema for the EM mixture regression algorithm such that it is free of initializations and can automatically obtain an approximately optimal number of clusters. Some numerical examples and comparisons demonstrate the superiority and usefulness of the proposed learning-based EM mixture regression algorithm.

Keywords: clustering, EM algorithm, Gaussian mixture model, mixture regression model

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Authors: Yong H Sheng, Beatriz Garcillán, Eden Whitlock, Yukli Freedman, SiLing Yang, M Arifur Rahman, Nicholas Weber, Fabienne Mackay

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Chronic lymphocytic leukemia (CLL) is closely associated with immune dysfunction, yet the mechanisms underlying this immune deficiency remain poorly understood. Transmembrane Activator and CAML Interactor (TACI), a receptor known for its role in IL-10 regulation and autoimmunity, to the best of our knowledge has not been investigated in the context of anti-tumor immunity or its impact on CLL progression. This study addresses the gap by exploring the role of TACI in regulating CLL cells within the tumor microenvironment and its broader effects on disease progression and immune competence. We utilized the Eµ-TCL1 mouse model to generate CLL mice deficient in TACI and examined the consequences of TACI loss in adoptive transfer models over a five-week period. Comprehensive transcriptomic analysis, including RNA sequencing and microarray, was employed to determine TACI’s influence on the CLL gene expression profile. Additionally, we studied TACI’s direct role in CLL cell migration and immune modulation using patient-derived CLL cells in culture and Patient-Derived Xenograph (PDX) models. Our findings demonstrate that TACI signaling plays a pivotal role in promoting CLL progression and immune suppression. Loss of TACI signaling significantly inhibited CLL development and enhanced immune functionality. When TACI+/+ or TACI-/- TCL1 CLL cells were transferred into wild-type recipient mice, those receiving TACI-deficient cells showed reduced disease progression and lower incidence of CLL. Mice with TACI-/- CLL cells exhibited normalized serum levels of pro-inflammatory cytokines IL-6 and IL-10, restored proportions of T-cell subsets, and improved immune compartment function compared to counterparts with TACI+/+ CLL cells. Mechanistically, TACI-deficient CLL cells expressed significantly lower levels of IL-10, TNF, and inhibitory receptors such as PD-L1 and PD-L2. These cells also display restored circulating immunoglobulin levels and responses to T cell-dependent antigens, highlighting a recovery of immune competence. Further mechanistic studies revealed that TACI signaling drives CLL cell migration and homing to the spleen, where these cells actively establish an immunosuppressive microenvironment that supports immune evasion and tumor growth. Patient-derived CLL cells and PDX models confirmed TACI’s direct role in enhancing CLL cell migration and fostering immune suppression, emphasizing its critical function in the tumor microenvironment. By disrupting TACI signaling, we observed a reduction in CLL-associated immune suppression and tumor progression, offering a promising therapeutic avenue. This study establishes, for the first time, that targeting TACI disrupts key mechanisms underlying CLL progression while preserving vital immune functions. Unlike existing treatments that often impair immunity and lead to infection-related complications, TACI inhibition offers the dual benefit of controlling disease and maintaining immune homeostasis. These findings provide a strong rationale for developing therapeutic strategies that inhibit TACI as a means to improve outcomes in CLL patients. Beyond its implications for CLL, this research underscores the broader importance of TACI in regulating immune-tumor interactions, paving the way for future studies into its role in other malignancies.

Keywords: chronic lymphocytic leukemia, TACI, IL-10, immune suppression

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Authors: Ammar Khader Almasri

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The software processes play a vital role for delivering a high quality software system that meets the user’s needs. There are many software development models which are used by most system developers, which can be categorized into two categories (traditional and new methodologies). Mobile applications like other desktop applications need appropriate and well-working software development process. Nevertheless, mobile applications have different features which limit their performance and efficiency like application size, mobile hardware features. Moreover, this research aims to help developers in using a standardized model for developing mobile applications.

Keywords: software development process, agile methods , moblile application development, traditional methods

Procedia PDF Downloads 387

Authors: Ali Kadivar, Kaveh Niayesh

Abstract:

This report summarizes a simulation-based approach to estimate the current interruption behavior of a fuse element utilized in a DC network protecting battery banks under different stresses. Due to internal resistance of the battries, the short circuit current in very close to the nominal current, and it makes the fuse designation tricky. The base configuration considered in this report consists of five fuse units in parallel. The simulations are performed using a multi-physics software package, COMSOL® 5.6, and the necessary material parameters have been calculated using two other software packages.The first phase of the simulation starts with the heating of the fuse elements resulted from the current flow through the fusing element. In this phase, the heat transfer between the metallic strip and the adjacent materials results in melting and evaporation of the filler and housing before the aluminum strip is evaporated and the current flow in the evaporated strip is cut-off, or an arc is eventually initiated. The initiated arc starts to expand, so the entire metallic strip is ablated, and a long arc of around 20 mm is created within the first 3 milliseconds after arc initiation (v_elongation = 6.6 m/s. The final stage of the simulation is related to the arc simulation and its interaction with the external circuitry. Because of the strong ablation of the filler material and venting of the arc caused by the melting and evaporation of the filler and housing before an arc initiates, the arc is assumed to burn in almost pure ablated material. To be able to precisely model this arc, one more step related to the derivation of the transport coefficients of the plasma in ablated urethane was necessary. The results indicate that an arc current interruption, in this case, will not be achieved within the first tens of milliseconds. In a further study, considering two series elements, the arc was interrupted within few milliseconds. A very important aspect in this context is the potential impact of many broken strips parallel to the one where the arc occurs. The generated arcing voltage is also applied to the other broken strips connected in parallel with arcing path. As the gap between the other strips is very small, a large voltage of a few hundred volts generated during the current interruption may eventually lead to a breakdown of another gap. As two arcs in parallel are not stable, one of the arcs will extinguish, and the total current will be carried by one single arc again. This process may be repeated several times if the generated voltage is very large. The ultimate result would be that the current interruption may be delayed.

Keywords: DC network, high current / low SC fuses, FEM simulation, paralle fuses

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Authors: Trude Tørset, María Díez Gutiérrez

Abstract:

The west coast of Norway features numerous islands and fjords. Ferry services connect the roads when these features make the construction challenging. Currently, scientific effort is designated to assess potential ferry replacement projects along the European road E-39. The inconvenience of ferry dependency is imprecisely represented in the transport models, thus transport analyses of ferry replacement projects appear as guesstimates rather than reliable input to decision-making processes of such costly projects. Trips including ferry connections imply more inconvenient elements than just travel time and cost. The goal of this paper is to understand and explain the extra inconveniences associated to the dependency of the ferry. The first scientific approach is to identify the characteristics of the ferry travelers and their trips’ features, as well as whether the ferry represents an obstacle for some specific trip types. In doing so, a survey was conducted in 2011 in eight E-39 ferries and in 2013 in 18 ferries connecting different road categories. More than 20,000 passengers answered with their trip and socioeconomic characteristics. The travel patterns in the different ferry connections were compared. The analysis showed that the trip features differed based on the location of the ferry connections, yet independently of the road category. Additionally, the patterns were compared to the national travel survey to detect differences in the travel patterns due to the use of the ferry connections. The results showed that the share of commuting trips within the same travel time was lower if the ferry was part of the trip. The second scientific approach is to know how the different travelers perceive potential benefits for a ferry replacement project. In the 2011 survey, some of the questions were about the relevance of nine different benefits this project might bring. Travelers identified the better access to public services and job market as the most valuable benefits, followed by the reduced planning of the trip. In 2016, a follow-up survey in some of the ferry connections was carried out in order to investigate variations in travelers’ perceptions. The growing interest in ferry replacement projects might make travelers more aware of the potential benefits these would bring to their daily lives. This paper describes the travel behaviour of travelers using a ferry connection as part of their trips, as well as the potential inconveniences associated to these trips. The findings might provide valuable input to further development of transport models, concept evaluations and cost benefit analysis methods.

Keywords: ferry connections, ferry trip, inconvenience costs, travel behaviour

Procedia PDF Downloads 227