Search results for: virtual physical model

Authors: Khitem Amiri, Mohamed Farah

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Image classification is a challenging task and is gaining lots of interest since it helps us to understand the content of images. Recently Deep Learning (DL) based methods gave very interesting results on several benchmarks. For Hyperspectral images (HSI), the application of DL techniques is still challenging due to the scarcity of labeled data and to the curse of dimensionality. Among other approaches, Deep Belief Network (DBN) based approaches gave a fair classification accuracy. In this paper, we address the problem of the curse of dimensionality by reducing the number of bands and replacing the HSI channels by the channels representing radiometric indices. Therefore, instead of using all the HSI bands, we compute the radiometric indices such as NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), etc, and we use the combination of these indices as input for the Deep Belief Network (DBN) based classification model. Thus, we keep almost all the pertinent spectral information while reducing considerably the size of the image. In order to test our image representation, we applied our method on several HSI datasets including the Indian pines dataset, Jasper Ridge data and it gave comparable results to the state of the art methods while reducing considerably the time of training and testing.

Keywords: hyperspectral images, deep belief network, radiometric indices, image classification

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Authors: Angela Maria Fasnacht

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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

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Authors: Ghodbane Azeddine, Saad Maarouf, Boland Jean-Francois, Thibeault Claude

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This paper proposes a new design of an active fault-tolerant flight control system against abrupt actuator faults. This overall system combines a multiple time scale sliding mode controller for fault compensation and a geometric approach for fault detection and diagnosis. The proposed control system is able to accommodate several kinds of partial and total actuator failures, by using available healthy redundancy actuators. The overall system first estimates the correct fault information using the geometric approach. Then, and based on that, a new reconfigurable control law is designed based on the multiple time scale sliding mode technique for on-line compensating the effect of such faults. This approach takes advantages of the fact that there are significant difference between the time scales of aircraft states that have a slow dynamics and those that have a fast dynamics. The closed-loop stability of the overall system is proved using Lyapunov technique. A case study of the non-linear model of the F16 fighter, subject to the rudder total loss of control confirms the effectiveness of the proposed approach.

Keywords: actuator faults, fault detection and diagnosis, fault tolerant flight control, sliding mode control, multiple time scale approximation, geometric approach for fault reconstruction, lyapunov stability

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Authors: Anu Vinod Ranade

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Aim: To evaluate and compare the effects of Vitamin C and Vitamin E on experimentally induced testicular torsion and detorsion in rats. Methods: Forty Male Wistar Albino rats were divided into five groups. Animals in the Group I underwent Sham operation, Group II consisted of animals that were subjected to torsion for three hours followed by detorsion for 24 hours without any treatment. While Group III, IV and V were orally pretreated with Vitamin C (40mg/kg.bw), vitamin E (100mg/kg.bw) and a combination of Vitamin C and vitamin E respectively for a period of 30 days. The testes of the experimental groups were manually rotated to 720° clockwise for three hours and counter rotated for 24 hours to induce ischemia and reperfusion. Sequential biopsies were performed and the testes were collected at the end of 24 hours of detrosion for morphological evaluation. Result: There was a significant decrease in the standard tubular diameter and the epithelial height of the seminiferous tubules in the untreated group when compared to Sham controls. The standard tubular diameter and seminiferous epithelial height showed near normal values when animals were pretreated with Vitamin C and Vitamin E individually or in combination. Conclusion: The results showed that pretreatment of with antioxidants vitamin E and vitamin C when administered prior to testicular torsion in rats significantly reduced the torsion and detorsion induced histopathlogical injury.

Keywords: vitamin C, vitamin E, standard tubular diameter, standard epithelial height, testicular torsion

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Authors: Gabriele Iannotta

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This paper investigates credit cycles by means of an experiment based on a Kiyotaki & Moore (1997) model with heterogeneous expectations. The aim is to examine how a credit squeeze caused by high lender-level risk perceptions affects the real prices of a collateralised asset, with a special focus on the macroeconomic implications of rising price volatility in terms of total welfare and the number of bankruptcies that occur. To do that, a learning-to-forecast experiment (LtFE) has been run where participants are asked to predict the future price of land and then rewarded based on the accuracy of their forecasts. The setting includes one lender and five borrowers in each of the twelve sessions split between six control groups (G1) and six treatment groups (G2). The only difference is that while in G1 the lender always satisfies borrowers’ loan demand (bankruptcies permitting), in G2 he/she closes the entire credit market in case three or more bankruptcies occur in the previous round. Experimental results show that negative risk-driven supply shocks amplify the volatility of collateral prices. This uncertainty worsens the agents’ ability to predict the future value of land and, as a consequence, the number of defaults increases and the total welfare deteriorates.

Keywords: Behavioural Macroeconomics, Credit Cycle, Experimental Economics, Heterogeneous Expectations, Learning-to-Forecast Experiment

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Authors: Emad Heydarnia, Aref Sepasi, Nika Asefi, Sara Khakshournia, Javad Mohammadnejad

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Background: Despite breakthrough therapeutics in breast cancer, it is one of the main causes of mortality among women worldwide. Thus, drug therapies for treating breast cancer have recently been developed by scientists. Metformin and Sorafenib are well-known therapeutic in breast cancer. In the present study, we combined Sorafenib and PCL-sorafenib with metformin to improve drug absorption and promote therapeutic efficiency. Methods: The MCF-7 cells were treated with Metformin, Sorafenib, or PCL-sorafenib. The growth inhibitory effect of these drugs and cell viability were assessed using MTT and flow cytometry assays, respectively. The expression of targeted genes involved in cell proliferation, signaling, and the cell cycle was measured by Real-time PCR. Results: The results showed that MCF-7 cells treated with Metformin/Sorafenib and PCL-sorafenib/Metformin co-treatment contributed to 50% viability compared to untreated group. Moreover, PI and Annexin V staining tests showed that the cells viability for Metformin/Sorafenib and PCL-sorafenib/Metformin was 38% and 17%, respectively. Furthermore, Sorafenib/Metformin and PCL-sorafenib/Metformin leads to p53 gene expression increase by which they can increase ROS, thereby decreasing GPX4 gene expression. In addition, they affected the expression of BCL2, and BAX genes and altered the cell cycle. Conclusion: Together, the combination of PCL-sorafenib/Metformin and Sorafenib/Metformin increased Sorafenib absorption at lower doses and also leads to apoptosis and oxidative stress increases in MCF-7 cells.

Keywords: breast cancer, metformin, nanotechnology, sorafenib

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Authors: Oladipo Joseph Ajayi, Yakubu Muhammed, Caleb Galadima

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This study was conducted to examine the income diversification of smallholder farmers in Bosso Local Government area of Niger state, Nigeria. The specific objectives were to examine the socio-economic characteristics of the farmers, identify the sources of income among the farmers, determine the pattern of income diversification and evaluate the determinants of income diversification of farmers in the study area. A multi-stage sampling technique was used to select 94 respondents for the study. Primary data were used, and these were collected with aid of a well structured interview schedule. Descriptive statistics, diversity index, and Tobit regression model were employed to analyze the data. The mean age of the farmers was 44 years. The average household size was 8 members per household, and the average farming experience was 12 years. 21.27 percent did not have formal education. It was further found that 69.1 percent of the respondents had an income diversity index of 0.3-0.4. This indicated that their level of income diversification was moderately low. The determinants of income diversification in the study area were education, household size, marital status, and primary income. These variables were positively related to income diversification. The study revealed that diversification into various income sources has helped to increase household income to sustain the family demands even though their level of income diversification was low within the study area.

Keywords: diversification, income, households, smallholder farmers

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Authors: Alaa Al Hawari, Mohammad Khader, Wael El Hasan, Mahmoud Alijla, Ammar Manawi, Abdelbaki Benamour

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The production of aluminium alloys and ingots -starting from the processing of alumina to aluminium, and the final cast product- was studied using a Life Cycle Assessment (LCA) approach. The studied aluminium supply chain consisted of a carbon plant, a reduction plant, a casting plant, and a power plant. In the LCA model, the environmental loads of the different plants for the production of 1 ton of aluminium metal were investigated. The impact of the aluminium production was assessed in eight impact categories. The results showed that for all of the impact categories the power plant had the highest impact only in the cases of Human Toxicity Potential (HTP) the reduction plant had the highest impact and in the Marine Aquatic Eco-Toxicity Potential (MAETP) the carbon plant had the highest impact. Furthermore, the impact of the carbon plant and the reduction plant combined was almost the same as the impact of the power plant in the case of the Acidification Potential (AP). The carbon plant had a positive impact on the environment when it comes to the Eutrophication Potential (EP) due to the production of clean water in the process. The natural gas based power plant used in the case study had 8.4 times less negative impact on the environment when compared to the heavy fuel based power plant and 10.7 times less negative impact when compared to the hard coal based power plant.

Keywords: life cycle assessment, aluminium production, supply chain, ecological impacts

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Authors: Steven D. P. Moore

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An electrical discharge in the air induces an electromagnetic (EM) wave capable of wireless transfer, reception, and conversion back into electrical discharge at a distant location. Following Norton’s ground wave principles, EM wave radiation (EMR) runs parallel to the Earth’s surface. Energy in an EMR wave can move through the air and be focused to create a spark at a distant location, focused by a receiver to generate a local electrical discharge. This local discharge can be amplified and stored but also has the propensity to initiate another EMR wave. In addition to typical EM waves, lightning is also associated with atmospheric events, trans-ionospheric pulse pairs, the most powerful natural EMR signal on the planet. With each lightning strike, regardless of global position, it generates naturally occurring pulse-pairs that are emitted towards space within a narrow cone. An EMR wave can self-propagate, travel at the speed of light, and, if polarized, contain vector properties. If this reflective pulse could be directed by design through structures that have increased probabilities for lighting strikes, it could theoretically travel near the surface of the Earth at light speed towards a selected receiver for local transformation into electrical energy. Through research, there are several influencing parameters that could be modified to model, test, and increase the potential for adopting this technology towards the goal of developing a global grid that utilizes natural sources of energy.

Keywords: electricity, sparkgap, wireless, electromagnetic

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Authors: Rajneesh, Priyanka Singh

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Biomass resources have been one of the main energy sources for mankind since the dawn of civilization. There is a vast scope to convert these energy sources into biogas which is a clean, low carbon technology for efficient management and conversion of fermentable organic wastes into a cheap and versatile fuel and bio/organic manure. Thus, in order to enhance the performance of anaerobic digester, an optimizing analysis of resultant parameters (organic dry matter (oDM) content, methane percentage, and biogas yield) has been done for a plug flow anaerobic digester having mesophilic conditions (20-40°C) with the wet fermentation process. Based on the analysis, correlations for oDM, methane percentage, and biogas yield are derived using multiple regression analysis. A statistical model is developed to correlate the operating variables using the design of experiment approach by selecting central composite design (CCD) of a response surface methodology. Results shown in the paper indicates that as the operating temperature increases the efficiency of digester gets improved provided that the pH and hydraulic retention time (HRT) remains constant. Working in an optimized range of carbon-nitrogen ratio for the plug flow digester, the output parameters show a positive change with the variation of dry matter content (DM).

Keywords: biogas, digester efficiency, design of experiment, plug flow digester

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Authors: Hui Zhang, Sherif Beskhyroun

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Structural Health monitoring systems (SHM) are commonly used to identify and assess structural damage. In terms of damage detection, SHM needs to periodically collect data from sensors placed in the structure as damage-sensitive features. This includes abnormal changes caused by the strain field and abnormal symptoms of the structure, such as damage and deterioration. Currently, deploying sensors on a large scale in a building structure is a challenge. In this study, a highly stretchable strain sensors are used in this study to collect data sets of strain generated on the surface of full-size reinforced concrete (RC) frames under extreme cyclic load application. This sensing sheet can be switched freely between the test bending strain and the axial strain to achieve two different configurations. On this basis, the deep neural network prediction model of the frame beam and frame column is established. The training results show that the method can accurately predict the strain value and has good generalization ability. The two deep neural network prediction models will also be deployed in the SHM system in the future as part of the intelligent strain sensor system.

Keywords: strain sensing sheets, deep neural networks, strain measurement, SHM system, RC frames

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Authors: Liza L. S. Choi

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Organizational burnout in higher education presents a critical challenge, undermining faculty well-being and institutional effectiveness. This study adopts a systemic perspective, addressing burnout through evidence-based strategies beyond individual coping mechanisms. Utilizing a meta-synthesis of existing literature, the author examines the underlying causes of burnout through the lenses of relational leadership, interpretivist theory, nudge theory, and the ADKAR model. The methodology synthesizes secondary data from peer-reviewed research, comprehensively analyzing key contributors to burnout, including excessive workloads, inadequate leadership, insufficient resources, and the absence of psychological safety. Key findings reveal that addressing burnout requires multi-faceted interventions. Effective implementation begins with leadership training programs grounded in relational leadership principles. These programs empower leaders to build trust by acknowledging and addressing faculty's unique challenges, such as workload inequities and insufficient support. For example, leaders can utilize interpretivist approaches to collect qualitative feedback through focus groups or anonymous surveys, providing actionable insights into the lived experiences of faculty. Institutions should establish policies encouraging open communication and normalizing feedback mechanisms to promote psychological safety. These initiatives include regular town halls, anonymous feedback portals, and structured team-building activities. They create environments where faculty feel supported and valued, reducing the stigma of voicing concerns. Drawing inspiration from successful practices in the healthcare sector, the author advocates for adopting an Associate Vice President (AVP) of Wellness role to lead organizational well-being initiatives. This role would centralize efforts to address faculty burnout and job satisfaction, ensuring alignment across departments and breaking down silos of operation. By fostering cross-departmental collaboration, this approach can lead to more integrated and efficient solutions, maximizing resource utilization and enhancing institutional resilience. The ADKAR model offers a structured framework for managing organizational change, emphasizing Awareness, Desire, Knowledge, Ability, and Reinforcement. Specific applications include facilitating workshops to raise awareness of burnout's impact, providing professional development programs that enhance faculty time management skills, and embedding well-being practices—such as flexible scheduling and equitable resource distribution—into institutional policies. Nudge theory further supports these efforts by employing subtle cues, such as reminders and default options, to encourage healthier work habits and foster collaboration. Finally, institutions should regularly evaluate the effectiveness of these interventions by implementing metrics such as faculty engagement scores, turnover rates, and utilization of wellness resources. By adopting a holistic and scalable framework that includes the AVP Wellness role and eliminates operational silos, this study provides academic institutions with practical tools to enhance morale, foster collaboration, and build resilience, ultimately addressing organizational burnout and creating a supportive educational environment.

Keywords: higher education, organizational burnout, relational leadership, culture of well-being and engagement

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Authors: N. Gigauri, V. Kukhalashvili, A. Surmava, L. Intskirveli, L. Gverdtsiteli

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Tbilisi, a large city of the South Caucasus, is a junction point connecting Asia and Europe, Russia and republics of the Asia Minor. Over the last years, its atmosphere has been experienced an increasing anthropogenic load. Numerical modeling method is used for study of Tbilisi atmospheric air pollution. By means of 3D non-linear non-steady numerical model a peculiarity of city atmosphere pollution is investigated during background western light air. Dust concentration spatial and time changes are determined. There are identified the zones of high, average and less pollution, dust accumulation areas, transfer directions etc. By numerical modeling, there is shown that the process of air pollution by the dust proceeds in four stages, and they depend on the intensity of motor traffic, the micro-relief of the city, and the location of city mains. In the interval of time 06:00-09:00 the intensive growth, 09:00-15:00 a constancy or weak decrease, 18:00-21:00 an increase, and from 21:00 to 06:00 a reduction of the dust concentrations take place. The highly polluted areas are located in the vicinity of the city center and at some peripherical territories of the city, where the maximum dust concentration at 9PM is equal to 2 maximum allowable concentrations. The similar investigations conducted in case of various meteorological situations will enable us to compile the map of background urban pollution and to elaborate practical measures for ambient air protection.

Keywords: air pollution, dust, numerical modeling, urban

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Authors: R. Jannat, N. S. Juyena, F. Y. Bari, M. N. Islam

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Understanding anatomy of female reproductive organs is very much important to identify any variation in disease condition. Therefore, this study was conducted to determine the morphometry of female reproductive tract in small ruminant using ultrasonography. The reproductive tracts of 2l does and 20 ewes were collected, and both gross and ultrasonographic image measurements were performed to study morphometry of cervix, body of uterus, horn of uterus and ovary. Water bath ultrasonography technique was used with trans-abdominal linear probe for image measurements. Results revealed significant (P<0.001) variation among gross and image measurements of cervix, body of uterus and ovaries in does whereas, significant (P<0.001) variation existed between gross and image measurements of ovaries diameter in ewes. Gross measurements were proportionately higher than image measurements in both species. The mean length and width were found higher in right ovaries than those of left ovaries. In addition, the diameter of right ovaries was higher than those of left ovaries in both species. Pearson's correlation revealed a positive relation between two measurements. Moreover, it was found that echogenicity varied with reproductive organs. This is a model study. This study may help to identify female reproductive structures by trans-abdominal ultrasonography.

Keywords: female reproductive tract, morphometry, small ruminants, ultrasonography

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Authors: Naniek Widayati Priyomarsono

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Introduction: In beginning of Karaton formation, namely, era of Javanese kingdom town had the power region outside castle town (called as Mancanegara), settlement of karaton can function as “the space-between” and “space-defense”, besides it was one of components from governmental structure and karaton power at that time (internal servant/abdi dalem and sentana dalem). Upon the Independence of Indonesia in 1945 “Kingdom-City” converted its political status into part of democratic town managed by statutes based on the classification. The latter affects local culture hierarchy alteration due to the physical development and events. Dynamics of social economy activities in Kampung Karaton surrounded by buildings of Complex of Karaton Kasunanan ini, have impact on the urban system disturbed into the región. Also cultural region image fades away with the weak visual access from existant cultural artefacts. That development lacks of giving appreciation to the established region image providing identity of Karaton Kasunanan particularly and identity of Surakarta city in general. Method used is strategy of grounded theory research (research providing strong base of a theory). Research is focused on actors active and passive relevantly getting involved in change process of Karaton settlement. Data accumulated is “Investigation Focus” oriented on actors affecting that change either internal or external. Investigation results are coupled with field observation data, documentation, literature study, thus it takes accurate findings. Findings: Karaton village has potential products as attraction, possessing human resource support, strong motivation from society still living in that settlement, possessing facilities and means supports, tourism event-supporting facilities, cultural art institution, available fields or development area. Data analyzed: To get the expected result it takes restoration in social cultural development direction, and economy, with ways of: Doing social cultural development strategy, economy, and politics. To-do steps are program socialization of Karaton village as Tourism Village, economical development of local society, regeneration pattern, filtering, and selection of tourism development, integrated planning system development, development with persuasive approach, regulation, market mechanism, social cultural event sector development, political development for region activity sector. Summary: In case the restoration is done by getting society involved as subject of that settlement (active participation in the field), managed and packed interestingly and naturally with tourism-supporting facilities development, village of Karaton Kasunanan Surakarta is ready to receive visit of domestic and foreign tourists.

Keywords: karaton village, finding, restoration, economy, Indonesia

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Authors: Qiao Mao

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There is a growing number of studies concerning STEM (Science, Technology, Engineering, and Mathematics) and STEAM (Science, Technology, Engineering, Arts, and Mathematics). However, the research is little on STEAM competitions from Arts' perspective. This study takes the annual PowerTech STEAM competition in Taiwan as an example. In this activity, students are asked to make wooden bionic mechanical beasts on the spot and participate in a model and speed competition. This study aims to explore how Arts influences STEM after it involves in the making of mechanical beasts. A case study method is adopted. Through expert sampling, five prize winners in the PowerTech Youth Science and Technology Creation Competition and their supervisors are taken as the research subjects. Relevant data which are collected, sorted out, analyzed and interpreted afterwards, derive from observations, interview and document analyses, etc. The results of the study show that in the PowerTech Youth Science and Technology Creation Competition, when Arts involves in STEM, (1) it has an impact on the athletic performance, balance, stability and symmetry of mechanical beasts; (2) students become more interested and more creative in making STEAM mechanical beasts, which can promote students' learning of STEM; (3) students encounter more difficulties and problems when making STEAM mechanical beasts, and need to have more systematic thinking and design thinking to solve problems.

Keywords: PowerTech, STEAM contest, mechanical beast, arts' role

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Authors: J. Joy, T. H. New, I. H. Ibrahim

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A computational study on bio-inspired NACA634-021 hydrofoils with leading-edge protuberances has been carried out to investigate their hydrodynamic flow control characteristics at a Reynolds number of 14,000 and different angles-of-attack. The numerical simulations were performed using ANSYS FLUENT and based on Reynolds-Averaged Navier-Stokes (RANS) solver mode incorporated with k-ω Shear Stress Transport (SST) turbulence model. The results obtained indicate varying flow phenomenon along the peaks and troughs over the span of the hydrofoils. Compared to the baseline hydrofoil with no leading-edge protuberances, the leading-edge modified hydrofoils tend to reduce flow separation extents along the peak regions. In contrast, there are increased flow separations in the trough regions of the hydrofoil with leading-edge protuberances. Interestingly, it was observed that dissimilar flow separation behaviour is produced along different peak- or trough-planes along the hydrofoil span, even though the troughs or peaks are physically similar at each interval for a particular hydrofoil. Significant interactions between adjacent flow structures produced by the leading-edge protuberances have also been observed. These flow interactions are believed to be responsible for the dissimilar flow separation behaviour along physically similar peak- or trough-planes.

Keywords: computational fluid dynamics, flow separation control, hydrofoils, leading-edge protuberances

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Authors: Kazuhisa Koda, Tsutomu Kobayashi

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Laura Island, which is located about 50 km away from downtown, is a source of water supply in Majuro atoll, which is the capital of the Republic of the Marshall Islands. Low and flat Majuro atoll has neither river nor lake. It is very important for Majuro atoll to ensure the conservation of its water resources. However, up-coning, which is the process of partial rising of the freshwater-saltwater boundary near the water-supply well, was caused by the excess pumping from it during the severe drought in 1998. Up-coning will make the water usage of the freshwater lens difficult. Thus, appropriate water usage is required to prevent up-coning in the freshwater lens because there is no other water source during drought. Numerical simulation of water usage applying SEAWAT model was conducted at the central part of Laura Island, including the water-supply well, which was affected by up-coning. The freshwater lens was created as a result of infiltration of consistent average rainfall. The lens shape was almost the same as the one in 1985. 0 of monthly rainfall and variable daily pump discharge were used to calculate the sustainable pump discharge from the water-supply well. Consequently, the total amount of pump discharge was increased as the daily pump discharge was increased, indicating that it needs more time to recover from up-coning. Thus, a pump standard to reduce the pump intensity is being proposed, which is based on numerical simulation concerning the occurrence of the up-coning phenomenon in Laura Island during the drought.

Keywords: freshwater lens, islands, numerical simulation, sustainable water use

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Authors: Tesfay Gebremichael Reda

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Nanoparticle technology is fast progressing and is being employed in innumerable medical applications. At this time, the public's health is seriously threatened by the rise of bacterial strains resistant to several medications. Metal nanoparticles are a potential alternate approach for tackling this global concern, and this is the main focus of this study. The citrate precursor sol-gel synthesis method was used to synthesize the, Niₓ Co(₁-ₓ) Fe₂ O₄, (where x = 0.0:0.2:1.0) nanoparticle. XRD identified the development of the cubic crystal structure to have a preferential orientation along (311), and the average particle size was found to be 29-38 nm. The average crystallizes assessed with ImageJ software and origin 22 of the SEM are nearly identical to the XRD results. In the created NCF NPs, the FT-IR spectroscopy reveals structural examinations and the redistribution of cations between octahedral (505-428 cm-1) and tetrahedral (653-603 cm-1) locales. Finally, the decrease of coercive fields HC, 2384 Oe to 241.93 Oe replacement of Co²+ cation with Ni²+. Band gap energy rises as Ni concentration increases, which may be attributed to the fact that the ionic radii of Ni²+ ions are smaller than that of Co²+ ions, which results in a strong electrostatic interaction. On the contrary, except at x = 0.4, the dielectric constant decreases as the nickel concentration increases. According to the findings of this research work, nanoparticles composed of Ni₀.₄ Co₀.₄ Fe₂ O₄ have demonstrated a promising value against S. aureus and E. coli, and it suggests a proposed model for their potential use as a new source of antibacterial agents.

Keywords: antimicrobial, band gap, citrate precursor, dielectric, nanoparticle

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Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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Authors: Vathna Suy, Ki-Il Song

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In order to store highly pressurized gas such as an isothermal compressed air energy storage, Lined Rock Caverns (LRC) are constructed underground and supported by layers of concrete, steel and rock masses. This study aims to numerically investigate the performance of rock masses which serve as a support of Lined Rock Cavern subjected to high cyclic pressure loadings. FLAC3D finite different software is used for the simulation since the software can effectively model the behavior of concrete lining and steel plate with its built-in structural elements. Cyclic pressure loadings are applied onto the inner surface of the cavern which then transmitted to concrete, steel and eventually to the surrounding rock masses. Changes of stress and strain are constantly monitored throughout all the process of loading operations. The results at various monitoring locations are then extracted and analyzed to assess the response of the rock masses, specifically on its ability to absorb energy during loadings induced by the changes of cyclic pressure loadings inside the cavern. By analyzing the obtained data of stress-strain relation and taking into account the behavior of materials under the effect of strain-dependency, conclusions on the performance of rock masses subjected to high cyclic loading conditions are drawn.

Keywords: cyclic loading, FLAC3D, lined rock cavern (LRC), strain-dependency

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Authors: Micheal O. Alabi

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Additive manufacturing (AM) is the official industry standard term (ASTM F2792) for all applications of the technology which is also known as 3D printing technology. It is defined as the process of joining materials to make objects from 3D model data, and it is usually layer upon layer, as opposed to subtractive manufacturing methodologies. This technology has gained significant interest within the academic, research institute and industry because of its ability to create complex geometries with customizable material properties. Despite the late adoption of the technology, additive manufacturing has been active in South Africa for past 21 years and it is predicted that additive manufacturing technology will play a significant and game-changing role in the fourth industrial revolution and in particular it promises to play an ever-growing role in efforts to re-industrialize the economy of South Africa. At the end of 2006, there are approximately ninety 3D printers in South Africa and in 2015 it was estimated that there are 3500 additive manufacturing systems and 3D printers in circulation in South Africa. A reasonable number of these additive manufacturing machines are in the high end of the market, in science councils and higher education institutions and this shows that the future of additive manufacturing in South Africa is very brighter compared to other African countries. This paper reviews the past and current industrial applications of additive manufacturing in South Africa from the academic research and industry perspective and what are the benefits of this technology to manufacturing companies and industrial sectors in the country.

Keywords: additive manufacturing, 3D printing technology, industrial applications, manufacturing

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Authors: Patcharakamon Nooeaid, Piyachat Chuysrinuan

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Electrospun natural polymers-based nanofibers are one of the most interesting materials used in tissue engineering and drug delivery applications. Bead-on-string nanofibers have gained considerable interest for sustained drug release. Vancomycin was used as the model drug and sodium alginate (SA)/soy protein isolated (SPI) as the polymer blend to fabricate the bead-on-string nanofibers by aqueous-based electrospinning. The bead-on-string SA/SPI nanofibers were successfully fabricated by the addition of poly(ethylene oxide) (PEO) as a co-blending polymer. SA-PEO with mass ratio of 70/30 showed the best spinnability with continuous nanofibers without the occurrence of beads. Bead structure formed with the addition of SPI and bead number increased with increasing SPI content. The electrospinning of 80/20 SA-PEO/SPI was obtained as a great promising bead-on-string nanofibers for drug loading, while the solution of 50/50 was not able to obtain continuous fibers. In vitro release tests showed that a more sustainable release profile up to 14 days with less initial burst release on day 1 could be obtained from the bead-on-string fibers than from smooth fibers with uniform diameter. In addition, vancomycin-loaded beaded fibers inhibited the growth of Staphylococcus aureus (S. aureus) bacteria. Therefore, the SA-PEO/SPI nanofibers showed the potential to be used as biomaterials for tissue engineering and drug delivery.

Keywords: bead-on-string fibers, electrospinning, drug delivery, tissue engineering

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Authors: Xinke Huang, Huan Wang, Lidong Guo, Changbin Ju, Runbiao Liu, Guoen Cao, Yibo Wang, Honghua Xu

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Grid connected photovoltaic (PV) power system is to be developed in the direction of large-scale, clustering. Large-scale PV generation systems connected to HVDC grid have many advantages compared to its counterpart of AC grid, and DC connection is the tendency. DC/DC converter as the most important device in the system, has become one of the hot spots recently. The paper proposes a Quasi Z-Source(QZS) based Boost Full Bridge Isolated DC/DC Converter(BFBIC) topology as a basis power module and combination through input parallel output series(IPOS) method to improve power capacity and output voltage to match with the HVDC grid. The topology has both traditional voltage source and current source advantages, it permit the H-bridge short through and open circuit, which adopt utility duty cycle control and achieved input current and output voltage balancing through input current sharing control strategy. A ±10kV/200kW system model is built in MATLAB/SIMULINK to verify the proposed topology and control strategy.

Keywords: PV Generation System, Cascaded DC/DC converter, HVDC, Quasi Z Source Converter

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Authors: Mohamed S. M. Elghazal, Adel Aneiba, Essa Q. Shahra

Abstract:

This study presents a comprehensive comparative analysis of REST and GraphQL API models within the context of microservices development, offering empirical insights into the strengths and limitations of each approach. The research explores the effectiveness and efficiency of GraphQL versus REST, focusing on their impact on critical software quality metrics and user experience. Using a controlled experimental setup, the study evaluates key performance indicators, including response time, data transfer efficiency, and error rates. The findings reveal that REST APIs demonstrate superior memory efficiency and faster response times, particularly under high-load conditions, making them a reliable choice for performance-critical microservices. On the other hand, GraphQL excels in offering greater flexibility for data fetching but exhibits higher response times and increased error rates when handling complex queries. This research provides a nuanced understanding of the trade-offs between REST and GraphQL API interaction models, offering actionable guidance for developers and researchers in selecting the optimal API model for microservice-based applications. The insights are particularly valuable for balancing considerations such as performance, flexibility, and reliability in real-world implementations.

Keywords: REST API, GraphQL AP, microservice, software development

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Authors: Ankur P. Sati, Manju Mohan

Abstract:

The hazardous combination of smoke and pollutant gases, smog, is harmful for health. There are strong evidences that the Agricultural waste burning (AWB) in the Northern India leads to adverse air quality in Delhi and its surrounding regions. A severe smog episode was observed over Delhi, India during November 2012 which resulted in very low visibility and various respiratory problems. Very high values of pollutants (PM10 as high as 989 µg m-3, PM2.5 as high as 585 µg m-3 an NO2 as high as 540 µg m-3) were measured all over Delhi during the smog episode. Ultra Violet Aerosol Index (UVAI) from Aura satellite and Aerosol Optical Depth (AOD) are used in the present study along with the output trajectories from HYSPLIT model and the in-situ data. Satellite data also reveal that AOD, UVAI are always at its highest during the farmfires duration in Punjab region of India and the extent of these farmfires may be increasing. It is observed that during the smog episode all the AOD, UVAI, PM2.5 and PM10 values surpassed those of the Diwali period (one of the most polluted events in the city) by a considerable amount at all stations across Delhi. The parameters used from the remote sensing data and the ground based observations at various stations across Delhi are very well in agreement about the intensity of Smog episode. The analysis clearly shows that regional pollution can have greater contributions in deteriorating the air quality than the local under adverse meteorological conditions.

Keywords: smog, farmfires, AOD, remote sensing

Procedia PDF Downloads 245

Authors: Tempe S. F. Adams, Michael J. Chase, Tracey L. Rogers, Keith E. A. Leggett

Abstract:

Transfrontier wildlife corridors can be successful conservation tools, connecting protected areas and reducing the impact of habitat fragmentation on mobile species. Urban wildlife corridors have been proposed as a potential mitigation tool to facilitate the passage of elephants through towns without causing conflict with urban communities. However, because such corridors are typically narrow and close to human development, wildlife (particularly large mammals) may be less likely to use them. We used remote-sensor camera traps and global positioning system collars to identify the movement patterns of African elephants Loxondonta africana through narrow, urban corridors in Botswana. The corridors were in three types of human-dominated land-use designations with varying levels of human activity: agricultural, industrial and open space recreational land. We found that elephants used the corridors within all three land-use designations and we identified, using a model selection approach, that season, time of day and rainfall were important factors in determining the presence of elephants in the corridors. Elephants moved more slowly through the narrow corridors compared with their movement patterns through broader, wide-ranging corridors. Our results indicate that urban wildlife corridors are useful for facilitating elephants to pass through urban areas.

Keywords: camera traps, conservation, human-elephant coexistence, land management, urban wildlife corridors

Procedia PDF Downloads 306

Authors: Regina Chua

Abstract:

To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

Procedia PDF Downloads 98

Authors: Jessie Rapoza, Petr Moroshkin, Jimmy Xu

Abstract:

Chirality is omnipresent, in nature, in life, and in the field of physics. One intriguing example is the homochirality that has remained a great secret of life. Another is the pairs of mirror-image molecules – enantiomers. They are identical in atomic composition and therefore indistinguishable in the scalar physical properties. Yet, they can be either therapeutic or toxic, depending on their chirality. Recent studies suggest a potential link between abnormal levels of certain D-amino acids and some serious health impairments, including schizophrenia, amyotrophic lateral sclerosis, and potentially cancer. Although indistinguishable in their scalar properties, the chirality of a molecule reveals itself in interaction with the surrounding of a certain chirality, or more generally, a broken mirror-symmetry. In this work, we report on a system for chiral molecule detection, in which the mirror-symmetry is doubly broken, first by asymmetric structuring a nanopatterned plasmonic surface than by the incidence of circularly polarized light (CPL). In this system, the incident circularly-polarized light induces a surface plasmon polariton (SPP) wave, propagating along the asymmetric plasmonic surface. This SPP field itself is chiral, evanescently bound to a near-field zone on the surface (~10nm thick), but with an amplitude greatly intensified (by up to 104) over that of the incident light. It hence probes just the molecules on the surface instead of those in the volume. In coupling to molecules along its path on the surface, the chiral SPP wave favors one chirality over the other, allowing for chirality detection via the change in an optical rectification current measured at the edges of the sample. The asymmetrically structured surface converts the high-frequency electron plasmonic-oscillations in the SPP wave into a net DC drift current that can be measured at the edge of the sample via the mechanism of optical rectification. The measured results validate these design concepts and principles. The observed optical rectification current exhibits a clear differentiation between a pair of enantiomers. Experiments were performed by focusing a 1064nm CW laser light at the sample - a gold grating microchip submerged in an approximately 1.82M solution of either L-arabinose or D-arabinose and water. A measurement of the current output was then recorded under both rights and left circularly polarized lights. Measurements were recorded at various angles of incidence to optimize the coupling between the spin-momentums of the incident light and that of the SPP, that is, spin-momentum locking. In order to suppress the background, the values of the photocurrent for the right CPL are subtracted from those for the left CPL. Comparison between the two arabinose enantiomers reveals a preferential signal response of one enantiomer to left CPL and the other enantiomer to right CPL. In sum, this work reports on the first experimental evidence of the feasibility of chiral molecule detection via optical rectification in a metal meta-grating. This nanoscale interfaced electrical detection technology is advantageous over other detection methods due to its size, cost, ease of use, and integration ability with read-out electronic circuits for data processing and interpretation.

Keywords: Chirality, detection, molecule, spin

Procedia PDF Downloads 95

Authors: Haowen Xi

Abstract:

We propose and solve exactly a class of non-linear generalization of the Black-Scholes process of stochastic differential equations describing price bubble and crashes dynamics. As a result of nonlinear positive feedback, the faster-than-exponential price positive growth (bubble forming) and negative price growth (crash forming) are found to be the power-law finite-time singularity in which bubbles and crashes price formation ending at finite critical time tc. While most literature on the market bubble and crash process focuses on the nonlinear positive feedback mechanism aspect, very few studies concern the noise level on the same process. The present work adds to the market bubble and crashes literature by studying the external sources noise influence on the critical time tc of the bubble forming and crashes forming. Two main results will be discussed: (1) the analytical expression of expected value of the critical time is found and unexpected critical slowing down due to the coupling external noise is predicted; (2) numerical simulations of the nonlinear stochastic equation is presented, and the probability distribution of Prob(tc) is found to be the inverse gamma function.

Keywords: bubble, crash, finite-time-singular, numerical simulation, price dynamics, stochastic differential equations

Procedia PDF Downloads 135