bluuebunny/crossref_metadata_2025 huggingface dataset:
Fault Diagnosis of Maritime Equipment Using an Intelligent Framework
Authors: Mendonça L.F. , Sousa J. M. C. , Vieira S. M.
Published: August 2024

The task of automatically and intelligently diagnosing faults in marine equipment is of great significance due to the numerous duties that shipboard professionals must handle. Incorporating automated and intelligent systems on ships allows for more efficient equipment monitoring and better decision-making. This approach has attracted considerable interest in both academia and industry because of its potential for economic savings and improved safety. Several fault diagnosis methods are documented in the literature, often involving mathematical and control theory models. However, due to the inherent complexity of some processes, not all characteristics are precisely known, making mathematical modeling highly challenging. As a result, fault diagnosis often depends on data or heuristic information. Fuzzy logic theory is particularly well-suited for processing this type of information. Therefore, this paper employs fuzzy models to diagnose faults in a marine pneumatic servo-actuated valve. The proposed fault diagnosis framework analyzes the discrepancy signals between the outputs of the fuzzy models and the actual process outputs. These discrepancies, known as residuals, help in detecting and isolating equipment faults. The fault isolation process uses an intelligent decision-making approach to determine the specific fault in the system. This method is applied to diagnose abrupt faults in a marine pneumatic servo-actuated valve.
Anti-Inflammatory Role of the Klotho Protein and Relevance to Aging
Authors: Prud'homme Gérald J. , Wang Qinghua
Published: August 2024

The α-Klotho protein (hereafter Klotho) is an obligate coreceptor for fibroblast growth factor 23 (FGF23). It is produced in the kidneys, brain and other sites. Klotho insufficiency causes hyperphosphatemia and other anomalies. Importantly, it is associated with chronic pathologies (often age-related) that have an inflammatory component. This includes atherosclerosis, diabetes and Alzheimer’s disease. Its mode of action in these diseases is not well understood, but it inhibits or regulates multiple major pathways. Klotho has a membrane form, and a soluble form (s-Klotho). Cytosolic Klotho is postulated but not well characterized. s-Klotho has endocrine properties that are incompletely elucidated. It binds to the FGF receptor 1c (FGFR1c) that is widely expressed (including endothelial cells). It also attaches to soluble FGF23, and FGF23/Klotho binds to FGFRs. Thus, s-Klotho might be a roaming FGF23 coreceptor, but it has other functions. Notably, Klotho (cell-bound or soluble) counteracts inflammation, and appears to mitigate related aging (inflammaging). It inhibits NF-κB and the NLRP3 inflammasome. This inflammasome requires priming by NF-κB, and produces active IL-1β, membrane pores and cell death (pyroptosis). In accord, Klotho countered inflammation and cell injury induced by toxins, damage-associated molecular patterns (DAMPs), cytokines, and reactive oxygen species (ROS). s-Klotho also blocks the TGF-β receptor and Wnt ligands, which lessens fibrotic disease. Low Klotho is associated with loss of muscle mass (sarcopenia), as occurs in aging and chronic diseases. s-Klotho counters the inhibitory effects of myostatin and TGF-β on muscle, reduces inflammation, and improves muscle repair following injury. Inhibition of TGF-β and other factors may also be protective in diabetic retinopathy and age-related macular degeneration (AMD). This review examines Klotho functions especially as related to inflammation, and potential applications.
Generalized core-EP inverse for triangular operator matrices
Authors: Chen Huanyin
Published: August 2024

We investigate the existence and representation of the generalized core-EP inverse of some triangular matrices over a Banach algebra. Further, the general representations of the generalized core-EP inverse of a triangular matrix over a $C^*$-algebra are presented. As applications, the generalized core-EP inverses of some block operator matrices over Hilbert spaces are given.
Three-dimensional Fuzzy Modeling for Nonlinear Distributed Parameter Systems Using Simultaneous Perturbation Stochastic Approximation
Authors: Zhang Xianxia , Wang Tangchen , Cheng Chong , Wang Shaopu
Published: August 2024

Many systems in the manufacturing industry have spatial distribution characteristics, which correlate with both time and space. Such systems are known as distributed parameter systems (DPS). Due to the spatiotemporal coupling characteristics, the modeling of such systems is quite complex. The paper presents a new approach for three-dimensional fuzzy modeling using Simultaneous Perturbation Stochastic Approximation (SPSA) for nonlinear DPS. The Affinity Propagation clustering approach is utilized to dynamically determine the optimal number of fuzzy rules and construct a collection of preceding components for three-dimensional fuzzy models. Fourier space base functions are used in the resulting components of three-dimensional fuzzy models, and their parameters are learned by the SPSA algorithm. The proposed three-dimensional fuzzy modeling technique was utilized on a conventional DPS within the semiconductor manufacturing industry, with the simulation experiments confirming its efficacy.
Structural Analysis and Experimental Tests of a Morphing Flap Scaled Model
Authors: SICIM DEMIRCI Mürüvvet Sinem , PECORA Rosario , CHIANESE Luca , Viscardi Massimo , KAYA Metin Orhan
Published: August 2024

The implementation of morphing wing mechanisms holds promise in enhancing aircraft perfor-mance, as indicated in current literature. The Clean Sky 2 AirGreen 2 European project is currently conducting ground and wind tunnel tests to validate innovative studies on morphing wing structures. The project aims to showcase the effectiveness of these morphing architectures on a potentially flying demonstrator at true scale. This article describes design methodology and struc-tural testing of a scaled morphing flap structure capable of 3 different morphing modes required for low-speed (take-off/landing) and high-speed (cruise) conditions. A significant scale factor of 1:3 was selected to enhance the importance and relevance of the wind tunnel test campaign. Geometrical scaling to the real flap prototype was deemed impractical due to limitations associated with scaling the embedded mechanisms and actuators responsible for shape changing. Static analyses were performed using the finite element method to address the most critical loads determined through three-dimensional CFD analysis. The Finite Element (FE) analysis results were briefly outlined, and comparisons were drawn between the obtained results and the empirical data collected during the structural test. Good correlations were observed between the results and numerical predictions, encompassing static deflections under applied loads and elastic deformations. Consequently, the modeling approaches utilized during the design and testing phases were considered highly suc-cessful. Therefore, based on the results extrapolated from simulations under ultimate load condi-tions relevant to the wind tunnel test campaign, the scaled flap prototype was deemed suitable for testing.
Convergence Rate of Regularized Regression Associated with Zonal Translation Networks
Authors: Ran Xuexue , Sheng Baohuai , Wang Shuhua
Published: August 2024

Neural network regularized learning has garnered significant attention in recent years. We give a systematic investigation on the performance of regularized regression associated zonal translation networks. We propose the concept of Marcinkiewicz-Zygmund inequality Setting (MZIS) for the scattered nodes collected from the unit sphere. We show that, under the MZIS, the corresponding convolutional zonal translation network has reproducing property. Based on these facts,we propose a kind of kernel regularized regression learning framework and provide upper bound estimate for the learning rate with the kernel approach. We also give proof for the density of the zonal translation network with spherical Fourier analysis.We provide the approximation error with a K-functional.
Return to Sports Activity in Individuals with Surgical Stomas: A Scoping Review
Authors: Mena-Jiménez Andrea-Victoria , Rodríguez-Suárez Claudio-Alberto , González-de la Torre Héctor
Published: August 2024

In surgically treated individuals with surgical stomas, the return to sports activity is an indicator of quality of life that reflects their well-being. With the aim of synthesizing the available evidence regarding the return to physical activity and sports practice in individuals with surgical stomas, a scoping review was developed following the methodological approach of the Joanna Briggs Institute and the Preferred Reporting Items for Systematic reviews and Meta-Analyses for Scoping Reviews criteria. Searches were conducted in Medline (PubMed), Scopus, Web of Science, Cinahl, and Lilacs, as well as the meta-search engines TripDatabase and Epistemonikos, using the MeSH terms "exercise", "return to sports", and "surgical stomas"; including studies in Spanish, English, Portuguese, and German, without any limitation on the year of publication. A total of n = 15 studies with different designs were included (n = 2 qualitative; n = 1 cohort; n = 8 cross-sectional; n = 2 case reports; n = 1 case series; and n = 1 Randomized Clinical Trial), which showed variability in the quality of the designs. The studies revealed the complex relationship between physical activity and having surgical stomas, associated with the individuals' characteristics. There is a need to increase the number and rigor of research to understand the phenomenon of return to physical activity and sport, thus providing evidence-based clinical recommendations for sports practice in people with stomas.
Promptology: Enhancing Human-AI Interaction in Large Language Models
Authors: Olla Phillip , Elliott Lauren , Abumeeiz Mustafa
Published: August 2024

The rapid integration of Generative AI technologies in academic and research environments marks the beginning of a new digital era, characterized by enhanced efficiency and innovative capabilities. This technological advancement, however, brings forth significant challenges and ethical dilemmas. One of the primary concerns is the potential diminishment of authentic human intellect in scholarly works, fueled by the capabilities of AI to generate ambiguous, fabricated, or even biased and inappropriate content. These issues highlight the critical need for developing comprehensive frameworks and establishing a dedicated field of study to govern the use of AI-generated content in academic and professional contexts.
This autoethnography explores the impact of generative AI on educational practices, detailing the development of the SPARRO framework in healthcare and nursing classes. Through personal reflections, interviews, and observations, it addresses specific challenges, offering insights into integrating GenAI ethically and effectively to enhance teaching and learning.
Local Defect Resonance: A Wild Card for NDT and Defect Imaging in Composites
Authors: Solodov Igor , Ehrler Julian , Littner Linus , Kreutzbruck Marc
Published: August 2024

The review considers physics and some applications of a new approach that promises to be a breakthrough in efficiency and instrumentation of various methods for nondestructive testing (NDT) of composites. The approach is based on frequency-selective properties of defects which fall into resonance (Local Defect Resonance (LDR)) at certain frequencies. An activation of LDR enables to route the input acoustic energy directly to the defect that dramatically increases its vibration amplitude and thus facilitates defect-selective imaging, rises efficiencies of various derivative acoustic NDT methods (nonlinear, acousto-thermal) and enables to develop some new methodologies, like Resonant Air-Coupled Emission (RACE), machine and remote imaging.
Evaluating Swarm Robotics for Diverse Mining Environments: Insights into Model Performance and Application
Authors: Tan Joven , Melkoumian Noune , Harvey David , Akmeliawati Rini
Published: August 2024

Mining industry is undergoing a revolution with the introduction of automation, especially through autonomous haul truck systems and is expected to have further essential developments due to advancements in swarm robotics and its applications. This study evaluates the performance of four different swarm robot models, i.e. baseline, ant, firefly, and honeybee, focusing on mining efficiency, scalability, reliability, and selectivity. Enhancements such as role specialization in the ant model, advanced communication in the firefly model, improved localization and the hybrid control system combining centralized and decentralized controls in the honeybee model are integrated to optimize their functionality. Mining simulations presented in this study include swarm robots of various designs, each resulting in certain advantages for autonomous operations. Their capabilities have been evaluated against performance criteria on a spider chart, identifying where each model excelled or failed in an actual extraction operation in mining. This study aims to identify the most optimal swarm models in relation to unique mining site conditions and goals. The applications of the suggested swarm models could contribute to achieving further improvement in productivity, scalability, selectivity and reliability, resulting in a more sustainable, automated and effective operations in mining.
Aflatoxin Contamination Association with Seed Coat Biochemical Markers in Peanut under Intermittent Drought
Authors: Aminou Maman Moutari , Falalou Hamidou , Mendu Venugopal , Abdou Harou
Published: August 2024

Aflatoxin contamination (AC) increases as the severity of drought stress increase in peanut. Identifying drought-tolerant (DT) genotypes with resistance to Aspergillus. flavus in semi-arid tropics may aid in development of peanuts that minimizing aflatoxin contamination. The goal is to identify the DT genotypes and resistant to aflatoxin contamination. The experiments curried out at ICRISAT Sahelian Center on fifty-five genotypes assessed in adjacent intermittent water-stressed (WS) from 60th day after sowing to maturity and well-watered (WW) conditions in a randomized complete block design. The yields and components, incidence of A. flavus colonisation, aflatoxin contamination and the seed coat total pthe olyphenol (SCTPP) were estimated. Water deficit reduced pod yield, seed yield, and haulm yield up to 19.49%, 27.24% and 22.07% respectively and increased the immature pods plant-1, (IMPN) and aflatoxin contamination up to 67.16% and 54.95%. The genotypes ICG 2106, ICG 311, ICG 4684, ICG 4543, and ICG 1415 maintained high yield under WS, less of IMPN and the lowest AC variation between WW and WS. The drought tolerant genotypes showed the relationship with aflatoxin resistance and SCTPP (r2=0.80; r2=0.82) under WW and WS. These findings can be used to select the genotype that combine drought tolerance and minimizing aflatoxin contamination.
Heat and Mass Transfer on MHD in the Oscillatory Flow of Viscoelastic Fluid between Two Plates with Heat Generation and Chemical Reaction
Authors: P Valsamy , B Chiranjeevi , G Vidyasagar
Published: August 2024

In this chapter we study the unstudy effect on MHD preamble porous medium through with thermal absorption and heat generation in the oscillatory flow of visco-elastic fluid between two plates in the presence of Chemical reaction. The expressions for the velocity, temperature and concentration distributions are arthemitiaclly solved by perturbation method.
Simulation of Necessary Macro TFP growth and Its Feasible Dual Circulation Source Pathways to Achieve China’s 2035 Economic Vision Goal: A Dynamic CGE Study
Authors: Qi Zike
Published: August 2024

By introducing final goods trade, intermediate goods trade, and factor-strengthening technology spillovers, along with technology absorption thresholds into the global value chain, this paper builds a global dynamic recursive general equilibrium model. This model can simulate China's technological progress driven by both 'internal' and 'external' (trade and FDI) dual circulations. Eight scenarios are employed to test and demonstrate whether China can follow the dual-circulation pattern and achieve the 2035 economic vision. The main conclusions are as follows:: (1) If China maintains its trade opening policy, the 2035 vision goal can be achieved, with external circulation being more important than internal for technological spillovers; (2) The economic growth impacts of external and internal circulations operate relatively independently. However, Foreign Direct Investment (FDI) provides a relatively larger synergistic effect to all forms of external trade circulation; (3) Regarding international trade partners, we find that RCEP is the most important strategic partner to China; (4) Apparently, FDI is not an effective way to lift the productive services sector's TFP, and China's realistic choice is to open the productive services market wider, as its efficiency is a pivotal reflection of China's independent innovation capability; (5) For factor-strengthening effects, spillovers are more favorable to 'capital' than to other kinds of labor; (6) The impact of China-US decoupling is enormous to the world. In all the scenarios we have envisioned, the United States is always the country that loses the most, and Europe would be the group of countries to benefit when there is a large increase of TFP in the US.
Symmetry in Formal Calculation
Authors: Peng Ji
Published: August 2024

Formal Calculation uses an auxiliary form to calculate various nested sums and provides results in three forms. It is also a powerful tool for analysis. This article studies the symmetry of the coefficients in Formal Calculation. Three types of extended numbers were introduced, and many formulas for symmetric functions were obtained.
School Counsellors’ Perspectives on the Loss of a Colleague: A Qualitative Study
Authors: Levkovich Inbar , Shira Tsundzer Meytar
Published: August 2024

Background: The loss of a co-worker always evokes complex emotions. Such a loss is particularly challenging for those who spend many hours at work and develop close interpersonal relationships with their colleagues. While many studies have examined how losing colleagues affects employees in various organizations, no research has specifically examined this topic in the school environment. Methods: This qualitative study explored the experiences of school counsellors facing the loss of colleagues from their school educational team. Twenty-one school counselors ranging in age from 28 to 61 who had lost a colleague within the past five years were examined by semi-structured in-depth interviews. The interviews were transcribed and analyzed using thematic content analysis. Results: Three main themes emerged from the data: (1) “From Shock to Action”: School Counsellors’ Reactions to Colleague Loss; (2) “From Friendship to Conflict”: School Counsellors' Diverse Experiences with Colleague Loss; and (3) “The Burden of Care”: Coping Mechanisms for School Counsellors Facing Colleague Loss. Conclusion: This study highlights the complex experiences of school counsellors in dealing with the death of colleagues. It underscores the importance of providing long-term emotional support for counsellors throughout their careers, particularly when coping with crises and emergencies.
Impact Resistance of Potential Replacement Materials for Large Power Transformer Tanks
Authors: Williams Jide , Hoffman Joseph , Predecki Paul , Kumosa Maciej
Published: August 2024

A recently published article posited the use of polymer matrix composites (PMCs) as a replacement material for low-carbon steel (LCS) in large power transformer (LPT) tanks [1]. PMCs offer potential advantages such as weight reduction, corrosion prevention, and self-healing of the tank material which may not be achievable with traditional LCS. LCS can arrest ballistic projectiles at relatively low velocities, but at higher velocities, penetration can occur leading to a potential major transformer failure. Numerical simulations of steel projectile impacts upon LCS plates and glass and/or carbon fiber polymer composite laminates showed that with sufficient thickness both could prevent projectile penetration. This prevention was especially efficient when the plates were coated with a high strain rate sensitive material such as polyurea (PU). Our simulations show that the addition of a 3 mm coating of PU to a standard 10 mm thick LCS plate used in LPT tanks could prevent penetration of a 400 m/s steel projectile. For PMC plates, the simulations with the same projectile velocity showed three times faster deceleration with a 3 mm PU coating than without the coating. Thus, two realistic approaches to improving the ballistic protection of LPTs are presented. In addition to their other advantages, this research clearly shows that PMCs with the coating could provide significant ballistic protection for the next generation of LPT tanks.
Impact of Walk, Transit, and Bike Scores on the “Alternative Transportation” Credit (LTc1) in LEED‐EB Version 4 (v4)‐Certified Projects in the United States
Authors: Pushkar Svetlana
Published: August 2024

This study aimed to evaluate the impact of the built environment (i.e., walk, transit, and bike scores) on the location and transportation or “alternative transportation” credit (LTc1) in Leadership in Energy and Environmental Design for Existing Buildings version 4 (LEED-EB-v4) Platinum (n1 = 24), Gold (n2 = 112), Silver (n3 = 46), and Certified (n4 = 34) office buildings in the USA. Spearman’s test was used to estimate the correlation between built environment scores and LTc1 scores for each certification level. The Wilcoxon–Mann–Whitney test was used to estimate pairwise comparison between unpaired Platinum, Gold, Silver, and Certified groups. The Platinum, Gold, and Silver certification levels showed positive and significant correlations between the built environment and LTc1 (0.44 ≤ r ≤ 0.74, p ≤ 0.0312). By contrast, Certified certification levels showed a non-significant correlation (0.18 ≤ r ≤ 0.33, p ≥ 0.0579). Pairwise comparison showed that Platinum and Gold groups outperformed Certified groups in terms of built environment and LTc1 scores (Cliff’s δ ≥ 0.37, p ≤ 0.0099). Thus, for LEED-EBv4-certified projects located in downtown areas, LTc1 can be seen as a significant lever to achieve high levels of LEED certification.
Modulatory Impact of Oxidative Stress on Membrane Action Potentials in Pathophysiological States: A Comprehensive Review
Authors: MAHAPATRA CHITARANJAN , Thakkar Ravindra , Kumar Ravinder
Published: August 2024

Oxidative stress, characterized by an imbalance between the production of reactive oxygen species (ROS) and the body's antioxidant defenses, significantly affects cellular function and viability. It plays a pivotal role in modulating action potentials (APs), essential for properly functioning excitable cells such as neurons, smooth muscles, pancreatic beta cells, and myocytes. The interaction between oxidative stress and AP dynamics is crucial for understanding the pathophysiology of various conditions, including neurodegenerative diseases, cardiac arrhythmias, and ischemia-reperfusion injuries. This review explores how oxidative stress influences APs, focusing on alterations in ion channel functionality, signaling pathways, and membrane properties. By integrating current research, we aim to elucidate how oxidative stress contributes to disease progression and discuss potential therapeutic interventions targeting this interaction.
Impact Evaluation of NO and SO2 Reduction by Biochar Characteristics
Authors: Choi Hyeonrok , Lee Yongwoon
Published: August 2024

Biochar has a carbon-based porous structure that is advantageous for adsorbing air pollutants. The pore structure of biochar ranges from several tens to hundreds of m²/g depending on the production temperature. We compared the pore characteristics of biochar with its NOx and SOx adsorption performances to evaluate its adsorbing potential. Biochar was produced from cypress biomass via slow pyrolysis in a fixed-bed reactor and CO2 partial gasification. Slow pyrolysis experiments at 500–700°C were conducted to produce biochar, followed by yield, proximate, elemental, and surface area analyses. CO2 partial gasification activated the biochar produced by slow pyrolysis at the same temperature, and similar analyses were performed. NO and SO2 adsorption experiments were conducted separately and together for biochar produced under each condition. Biochar produced at 600°C showed the highest specific surface area. CO2 partial gasification increased the surface area at each temperature, reaching 680.3 m²/g at 700°C. In single adsorption experiments, N2 carbonized biochar showed NO and SO2 adsorption efficiencies of 84–90% and 88.2–91.4%, respectively, with similar trends in simultaneous adsorption experiments. CO2 activated biochar exhibited higher adsorption efficiencies due to its increased surface area, with NO and SO2 adsorption at 89.8–93.9% and 92–98.9%, respectively. Biochar activated at 700°C simultaneously adsorbed approximately 99% NO and SO2. The NO adsorption efficiency increased with increasing surface area of the small pores, whereas the SO2 adsorption efficiency improved with the development of both small and large pores.
Water Quality Benefits of Porous Pavement on Major Arterial Roads
Authors: Holzer Katie , Poor Cara
Published: August 2024

Stormwater runoff from large roads is a major source of pollutants to receiving waters. Porous pavements have been shown to substantially reduce many of these pollutants, but studies are lacking on arterial roads. We sampled typical stormwater pollutants in runoff from sections of an arterial road 9-16 years after installation of three pavement types: control with conventional asphalt, porous asphalt overly, and full-depth porous asphalt. Both types of porous pavements substantially reduced most of the stormwater pollutants measured. Total suspended solids, turbidity, total lead, total copper, and 6PPD-quinone were all reduced by >75%. Total nitrogen, ammonia, total phosphorus, biochemical oxygen demand, total and dissolved copper, total mercury, total zinc, total polycyclic aromatic hydrocarbons, and di-2-ethylhexyl phthalate were all reduced by >50%. Reductions were lower or absent for nitrate, orthophosphate, E. coli, dissolved lead, and dissolved zinc. Most reductions were statistically significant. Many pollutants exceeded applicable water quality standards in the control samples but met them with both types of porous pavement. This study demonstrates that porous overlays and full-depth porous asphalt can provide substantial reductions of several priority stormwater pollutants on arterial roads for many years after installation.
Building Digital Twin Data Model based on Public Data
Authors: Jeong Dawoon , Lee Changyoon , Choi Youngmin , Jeong Taeyun
Published: August 2024

This study aims to propose a method for constructing basic digital twin data in South Korea by adhering to international standards and utilizing publicly available data. Specifically, the study focuses on designing and proposing a digital twin data model for buildings, which are the most applicable among the basic digital twin data. To achieve this, the first section provides essential background information, introduces concepts and requirements related to digital twin basic data, and offers a brief overview of CityGML. The second section explains the methodology and data used in this study. The third section presents the main findings: the selection of public data (buildings) for constructing digital twin basic data, the mapping process using CityGML, and the creation of UML diagrams. The fourth section discusses these findings. Finally, the conclusion and suggestions for future research are provided. This approach enhances the accuracy of building-related digital twin data and supports the use of digital twin services in both public and private sectors by enabling various spatial analyses.
A Methodology to Evaluate the Horizontal Earth Pressure Acting on Circular Shafts Based on Its Lateral Displacements
Authors: Pedro António M. G.
Published: August 2024

One of the most common solutions to access underground is through the construction of circular shafts. At preliminary design stage analytical expressions are often used to estimate the horizontal earth pressure acting on the lining. However, most of these solutions are based on active state conditions and do not consider the restrictions imposed on the shaft lateral displacements by the rigidity of its lining or by the construction method employed. To overcome this limitation a new methodology to account with the shaft lateral displacements in the determination of the horizontal earth pressure acting on circular shafts is developed and validated against the results of relevant physical scale models. The obtained results show good agreement with the measured data, reproducing adequately the reduction of the horizontal earth pressure from its initial value to an active state condition with the increase of the shaft lateral displacement. Following this approach more realistic predictions of the earth pressure acting on the lining of circular shafts can be performed.
Weibull Random Vibration Reliability Based on Cumulated Damage
Authors: Hernández-Ramos María M. , Piña-Monarrez Manuel R. , Barraza-Contreras Jesús M. , Monclova-Quintana Osvaldo
Published: August 2024

In this paper, based on the cumulated damage generated by the cyclical application of the testing vibration profile, a methodology to determine the reliability index of the analyzed component is given. In the analysis, the testing time, component geometry, applied weight, and material resonant frequency are all of them considered by using a dynamic, and amplitude factor. Then, from the generated vibration response data of the analysis, the corresponding bending stress is determined for each one of the rows of the testing profile. And by the cyclical application of the whole testing profile, the corresponding damage is cumulated to each profile cycle until the cumulated damage is D=1. Finally, the reliability that each one of the cumulated blocks (cyclical profile application) is determined by considering, the random vibration is a stress variable. Thus, we use the cumulative damage model with the inverse power law stress/life relationship to determine the two parameter Weibull distribution used to estimate the reliability index of each cumulated block. As a numerical application, we analyze a cantilever aluminum beam Al 6061-T6.
Enhanced Microgrid Control through Genetic Predictive Control: Integrating Genetic Algorithms with Model Predictive Control for Improved Non-Linearity and Non-Convexity Handling
Authors: Cavus Muhammed , Allahham Adib
Published: August 2024

Microgrid (MG) control is essential for efficient, reliable, and sustainable energy management in distributed energy systems. Genetic Algorithm-based energy management systems (GA-EMS) can optimally control a MG by finding global optima and handling complex, non-linear, and non-convex problems, but they can be computationally intensive, making real-time control challenging. Model Predictive Control (MPC)-based EMS predicts future behaviour over a defined horizon, ensuring optimal performance and constraint satisfaction but typically relies on linear models. This paper proposes a novel Genetic Predictive Control (GPC) method, combining GA and MPC to enhance resource allocation, balance multiple objectives, and adapt dynamically to changing conditions. Integrating GA with MPC significantly improves the handling of non-linearities and non-convexity in the system model, leading to more accurate and effective control. Comparative analysis shows that GPC significantly reduces excess power production—surplus power generated beyond load demand—improving resource allocation efficiency. For instance, in the Mutation–Random Selection scenario, GPC reduced excess power to 76.0W compared to 87.0W with GA. Additionally, GPC balances cost, emissions, and power efficiency. In the Crossover-Elitism scenario, GPC achieved a daily cost of $113.94 compared to GA's $127.80, and carbon emissions of 52.83 kg CO2e compared to GA's 69.71 kg CO2e, demonstrating GPC's cost efficiency and environmental benefits. While MPC optimizes a weighted sum of objectives, designing appropriate weights can be challenging and may result in non-convex problems. GA handles multiple, conflicting objectives through multi-objective optimization, providing Pareto-optimal solutions. GPC's dynamic adaptability maintains optimal performance by forecasting future load demands and adjusting control actions. GPC consistently achieves lower emissions than GA across various scenarios and, although it sometimes incurs higher costs, such as $113.94 compared to $131.90 in the Crossover–Random Selection scenario, its holistic approach balances these costs with other metrics, making it cost-effective in the long run. By reducing excess power production and emissions, GPC contributes to economic savings and promotes sustainable practices. These findings underscore GPC's potential as a versatile, efficient, and environmentally beneficial optimization tool for power generation systems.
Navigating the Grey Area: Students' Ethical Dilemmas in Using AI Tools for Coding Assignments
Authors: Mutanga Bethel Murimo , Lecheko Matthews , Revesai Zvinodaishe
Published: August 2024

Integrating artificial intelligence (AI) in higher education, particularly in coding assignments for Information Technology (IT) students, represents a rapidly evolving research area with significant implications for academic practices and integrity. This study focuses on the ethical challenges faced by IT students when using AI tools like ChatGPT for coding assignments. Despite the growing use of AI in education, there is a notable gap in understanding how students perceive and navigate the ethical dilemmas associated with these technologies. To address this gap, this study employed a thematic analysis of qualitative data collected from interviews with IT students. The results reveal a complex landscape of ethical considerations, including issues of originality, academic integrity, and the potential for misuse of AI tools. Students reported challenges in balancing the benefits of AI assistance with the need to maintain independent learning and adhere to ethical standards. The implications of this research are significant for educators, institutions, and policymakers. Understanding the ethical challenges students face can inform the development of more effective teaching strategies, assessment methods, and institutional policies. This study contributes to the ongoing dialogue about AI ethics in academia, providing valuable insights for creating an educational environment that leverages the power of AI while upholding the principles of academic integrity and meaningful learning.
ANALISIS EFEKTIVITAS PEMBELAJARAN JARAK JAUH MENGGUNAKAN MICROSOFT TEAMS PADA MATA KULIAH JARINGAN KOMPUTER DI UNIVERSITAS NEGERI JAKARTA DENGAN QAIT MODEL
Authors: Ariq Adiwidya  , M. Ficky Duskarnaen  , Hamidillah Ajie
Published: August 2024

Dalam pelaksanaan Pembelajaran Jarak Jauh selama pandemi Covid-19, terdapat berbagai kendala yang terjadi, tidak terkecuali di Universitas Negeri Jakarta. Hal tersebut diatasi salah satunya dengan penggunaan Learning Management System. Penelitian ini bertujuan untuk menganalisis dan mengetahui efektivitas Pembelajaran Jarak Jauh menggunakan Microsoft Teams sebagai alternatif Learning Management System pada Mata Kuliah Jaringan Komputer di Universitas Negeri Jakarta dengan metode QAIT Model. Metode yang digunakan adalah penelitian survei dengan pendekatan kuantitatif dengan subjek penelitian mahasiswa aktif Universitas Negeri Jakarta yang sedang dan sudah mengambil Mata Kuliah Jaringan Komputer pada masa Pembelajaran Jarak Jauh. Dari hasil penelitian dapat disimpulkan bahwa efektivitas pembelajaran jarak jauh menggunakan Microsoft Teams pada Mata Kuliah Jaringan Komputer di Universitas Negeri Jakarta secara keseluruhan memiliki skor Derajat Pencapaian sebesar 82,01% dan berada pada kategori “Baik”.
Low Resistivity Pay Zone Detection in Hydrocarbon Formation: The Feasibility of the Spectral Induced Polarization Method
Authors: Kellal S. , Kirmizakis P. , El-Husseiny A. , Ntarlagiannis D. , Soupios P. , Mahmoud M.
Published: August 2024

Identifying and characterizing low resistivity pay (LRP) zones within hydrocarbon-rich formations has long been challenging in the petroleum industry due to their complex mineral composition, microporosity, and diminished resistivity contrasts. Traditional methods, such as resistivity measurements, struggle to effectively pinpoint LRP zones, prompting the need for innovative approaches in reservoir evaluation. This paper explores the feasibility of using the spectral induced polarization (SIP) method for detecting LRP zones. The SIP method measures complex conductivity across a frequency range from 1 mHz to 10 kHz. While this technique has been widely used in mining and environmental studies, its potential for petrophysics applications in the oil and gas sector remains largely unexplored. This study acts as a proof of concept, demonstrating the capability of SIP for detecting LRP zones. Laboratory experiments utilized dual-porosity silica gel samples with controlled micro- and macroporosity fractions and added pyrite content. Despite a high crude oil saturation of approximately 60%, the presence of brine in continuous micropores resulted in low resistivity readings (0.7 Ω·m) at low frequencies, as conventionally measured by direct current resistivity tools. However, at higher frequencies (>100 Hz), the study observed high average resistivity values (82 Ω·m), indicating a frequency-dependent behavior in electrical measurements. This behavior is attributed to polarization mechanisms, including the electrical double layer (EDL). This study’s findings propose the SIP method’s potential effectiveness for detecting LRP zones, paving the way for future research to delve deeper into the application of SIP in petrophysics.
WITHDRAWN: Advancing Environmental Monitoring: Unveiling Heavy Metal Contamination with Calibration-Free Picosecond Laser-Induced Breakdown Spectroscopy (CF-PS-LIBS)
Authors: Fayek Noura , Tawfik Walid , KhalafAllah Ahmed , Fikry Mohamed
Published: August 2024

The full text of this preprint has been withdrawn by the authors while they make corrections to the work. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
Effect of Artificial Intelligence on Economic Growth in European Countries: a symmetric and asymmetric cointegration based on linear and non-linear ARDL approach
Authors: KALAI Maha , BECHA Hamdi , ABDALLAH Amal Ben , HELALI Kamel
Published: August 2024

In recent years, the Artificial Intelligence (AI) emergence had an important impact on the global economy, especially in advanced countries. Therefore, this study assessed the AI effect on economic growth in 30 European countries between 2000 and 2021 using the symmetric (PMG-ARDL) model and the asymmetric (PMG-NARDL) model. The results of this study lead us to conclude that the use of AI in the ARDL model has a positive impact on economic growth. Specifically, an increase in the AI variable leads to a 0.217% increase in economic growth in the long run. In the case of the NARDL model, positive shocks to the positive AI variable led to an increase in economic growth, but negative shocks reduce it. The use of this technology can stimulate economic growth by increasing efficiency, fostering economies of scale, improving the quality of products and services and creating better working conditions. However, it can also have negative effects, such as job displacement, training and adaptation costs and the exacerbation of economic and social inequalities. Hence, policymakers are urged to examine AI role in driving economic growth and fostering inclusive development, particularly in sectors where it can facilitate the creation of AI-based solutions to tackle social and environmental challenges.
JEL Classification: C23; O31; O11.
The Relationship between CO2 Emissions, Economic Growth, Labor Force, Digitalization, Urbanization and Renewable Energy Consumption: Evidence from the EU and Selected Developing Countries
Authors: Akyol Hikmet , AĞIRKAYA Melahat BATU
Published: August 2024

This research deals with the relationship between CO2 emissions and economic growth, labor force, digitalization, urbanization rate, and renewable energy consumption. In this context, the period covering 1994–2020 in 26 European Union (EU) member states and nine leading developing countries was estimated using Pearson correlation, panel cointegration, regression, and heterogeneous causality analyses. Research findings have shown that economic growth increases CO2 emissions and environmental degradation. The analysis estimates showed the negative impact of economic growth on environmental quality in both EU members and developing countries. For this reason, the dissemination of environmentally friendly production and techniques is necessary for both groups of countries. At the panel level, the impact of the workforce on CO2 emissions is positive. We found that renewable energy consumption increases environmental quality for both groups of countries. The findings, both by the panel and by country, on the impact of urbanization and digitalization on CO2 emissions are complex. The results revealed that environment-based digital transformation is not at the desired level for most countries in the sample. Causality analysis showed a bidirectional causality between growth, labor, and CO2 emissions. There is a one-way causality from digitalization, urbanization rate, and renewable energy consumption to CO2 emissions.
Homeopathic Additives and Yeast on the Performance of Pantaneira Heifers Maintained in a Rotational Grazing System
Authors: Florentino Leandra da Silva , Silva Evellyn Richelly Ferreira da , Queiroz Maria Carla Elias , Torgan Daniele Portela de Oliveira , Júnior Fernando Miranda de Vargas , Luz Dirce Ferreira , de Oliveira Dalton Mendes , de Oliveira Marcus Vinícius Morais
Published: August 2024

The present study aimed to evaluate the effects of using homeopathic products combined with yeast (Saccharomyces cerevisiae) on the performance of Pantaneira heifers in a rotational grazing system on Mombaça grass (Megathyrsus maximus) in the Pantanal biome during the spring season. The treatments analyzed were Control (CTL) and Homeopathic combined with Yeast (HY). A total of 20 animals were randomly allocated, with 10 heifers in each treatment group. Animal performance was evaluated through forage and supplement intake, diet digestibility, weight gain, and feed conversion ratio. The experimental design was completely randomized, and the means were compared using Tukey and Duncan tests at a 5% probability level. No significant effects were identified between the treatments on total feed intake, expressed in kg/day, metabolic weight, and percentage of body weight (P ≥ 0.05), concentrate and grass intake (P ≥ 0.05), neutral detergent fiber intake (P ≥ 0.05), final body weights, average daily gain, and feed conversion ratio (P ≥ 0.05). However, it was observed that heifers in the HY treatment showed significantly higher digestibility rates of dry matter, crude protein, and neutral detergent fiber (P ≤ 0.05), as well as higher digestibility of non-fibrous carbohydrates, ether extract, and mineral matter (P ≤ 0.05), although the levels of Total Digestible Nutrients and Digestible Energy were similar to the CTL treatment (P ≥ 0.05). It is concluded that the combination of homeopathy and yeast provided better utilization of the fibrous components of the diet by the animals.
Climate-Driven Changes in Freshwater Inputs to a northern Patagonia Fjord and overfishing of wild mussel seed could threaten Chilean mussel farming
Authors: molinet carlos , Soto Doris , León-Muñoz Jorge , Díaz Manuel , Espinoza Katherine , Henríquez Jorge , Matamala Thamara
Published: August 2024

Chile is the first world exporter of farmed mussels with an annual harvest about 400000 tones, such production is based on the capture of wild seed which availability may be threatened by climate change and overfishing. Climate change-induced decreasing trends in annual precipitation, which increases water column salinity and this could be affecting the vertical distribution of mussel populations in fjords. In the Reloncaví Fjord, Chile, the observed changes in precipitation reduce the freshwater inputs, leading to potential shifts in the habitat and distribution of the economically significant Chilean mussel (Mytilus chilensis) and a competing species, Aulacomya atra. This research analyzes mussel beds' vertical dynamics in relation to changing environmental conditions, including freshwater inputs, salinity, and hydrological regimes in an exploited fjord for mussel seed collection. The findings suggest that decreasing trends in precipitation could result in increased surface salinity, reducing M. chilensis beds while favouring A. atra, with negative consequences for wild seed collection therefore threatening the Chilean mussel farming industry, projecting socio-economic impacts for small-scale aquaculture. Also, this study describes the increasing fishing pressure for wild mussel larvae and suggesting joint effects which are not possible to untangle with the present information and represents a key challenge for the design of adaptation measures for climate change. Therefore, this study emphasizes the need for better monitoring of mussel beds along with seed production and oceanographic conditions as well as improving aquaculture practices that reduce unnecessary pressure on mussel beds through seed collection in the face of changing environmental conditions.
Polyolefin Reweaved Ultra-micropore Membrane for CO2 Capture
Authors: Liu Gongping , Chen Xiuling , Chen Guining , Wu Lei , Li Nanwen , Jin Wanqin , Xie Cong
Published: August 2024

High-performance gas separation membranes have potential in industrial separation applications, while overcoming the permeability-selectivity trade-off via regulable aperture distribution remains challenging. Here, we report a novel strategy to fabricate Polyolefin Reweaved Ultra-micropore Membrane (PRUM) to acquire regulable microporous channel. Specifically, olefin monomers are dispersed uniformly into a pristine membrane (e.g., PIM-1) via solution diffusion method. Upon controlled electron beam irradiation, the olefin undergoes a free radical polymerization, resulting in the formation of olefin polymer in-situ reweaved in the membrane. The deliberately regulated and contracted pore-aperture size of the membrane can be accomplished by varying the olefin loading to achieve efficient gas separation. For instance, PIM-1 PRUM containing 27wt% poly-methyl methacrylate demonstrate CO2 permeability of 1976 Barrer, combined with CO2/CH4 and CO2/N2 selectivities of 58.4 and 48.3 respectively, transcending the performance upper bounds. This controllable and high efficiency-design strategy provides a general approach to create sub-nanometre-sized pore-apertures of gas separation membranes with wide universality.