bluuebunny/crossref_metadata_2025 huggingface dataset:
PENGARUH JENIS DAN KONSENTRASI SUBSTRAT TAMBAHAN TERHADAP PROSES PENGOLAHAN AIR BUANGAN SECARA ANAEROBIK
Authors: Primasari Budhi , Nur Ansiha
Published: February 2025

ABSTRAKPenelitian ini menyelidiki pengaruh penambahan glukosa, fruktosa dan sukrosa terhadap pengolahan air buanganrumah tangga dengan proses mikroba anaerobik menggunakan reaktor batch. Parameter yang diamati adalahCOD (Chemical Oxygen Demand), TSS (Total Suspended Solid), VSS (Volatile Suspended Solid) dand volumebiogas. Proses pengolahan dievaluasi dari jumlah polutan yang berkurang dan jumlah biogas yang terbentuk.Tiga jenis gula dengan kisaran konsentrasi yang bervariasi ditambahkan ke lumpur sebelum proses pengolahanair buangan. Proses pengolahan itama adalah proses fermentasi gelap anaerobik, dengan reaktor aerobikdiguncang di atas shaker pada kecepatan 200 rpm.Ph diatur menjadi 5 dan suhu 30oC. Hail menunjukkan bahwaglukosa dengan jumlah biakan bakteri 20%, dan konsentrasi guil 2% adalah substrat tambahan yang pling efisien,mengurangi kadar COD hampir 100%. Volume biogas yang dihasilkan 9,5 mL dan TSS serta TSS adalah 37 mg/Ldan 460 mg/L.Kata kunci: glukosa, sukrosa, fruktosa, substrat, pengolahan air buanganABSTRACTThis research investigate effects of addition of glucose, sucrose dan fructose to the sewage wastewater treatmentprocess by anaerobic microbial process using batch reactor. The observed parameters are COD (ChemicalOxygen Demand), TSS (Total Suspended Solid), VSS (Volatile Suspended Solid) and volume of biogas. Thetreatment process was evaluated by reduction of pollutant and biogas production. Three types of sugar at a rangeof concentration was added to the sludge prior to wastewater treatment . The main treatment was anaerobic darkfermentation process, shaken at 200 rpm. pH was set to be 5 and temperature was 30oC. The results shows thatglucose at 20% inoculum size and 2% sugar concentnration in the most efficient substrate, reduced COD to almost1005. The volume of biogas produced is 9.5 mL, and TSS and VSS were 37 mg/L and 460 mg/L respectively.Keywords: glucose, sucrose, fructose, substrate, wastewater treatment
Educational design of the course "Business interpretation in the Russian-Chinese language combination" in the era of artificial intelligence (using the example of ChatGPT)
Authors: Yue Ruiying
Published: February 2025

The advent of ChatGPT opens up new opportunities for improving the teaching methods of business interpretation, especially in such a complex language combination as Russian-Chinese. Despite significant progress in the field of machine translation, the role of a human translator remains indispensable, especially in the field of business interpretation, where a deep understanding of the cultural context and features of intercultural communication is required. In this regard, there is a need to develop new approaches to training translators that will effectively integrate the capabilities of artificial intelligence into the educational process while maintaining the focus on developing students' professional competencies. In the context of the rapid development of artificial intelligence technologies and their integration into the educational process, the issue of effective use of modern digital tools in the training of professional translators is becoming particularly relevant. The subject of the research is the method of integrating artificial intelligence into the process of teaching business interpretation. The research methodology is based on the integrated application of qualitative and quantitative methods, including longitudinal observation, in-depth interviews with experts, and statistical analysis of learning outcomes. The scientific novelty of the research is the development of an innovative teaching methodology for business interpretation in a Russian-Chinese language combination with the integration of artificial intelligence technologies. For the first time, a comprehensive approach to using ChatGPT as a multifunctional tool in the educational process has been proposed, including a system of specially designed exercises and methods for assessing translation competencies. An original modular course structure has been developed that combines traditional teaching methods with artificial intelligence capabilities to create authentic business communication situations. A unique method of designing educational assignments using ChatGPT has been created, based on the principle of gradual complication of the material and taking into account the specifics of Russian-Chinese business communication. The effectiveness of the developed approach has been empirically proven through a system of longitudinal observation and statistical analysis of learning outcomes. The results of the study demonstrate a significant increase in the effectiveness of the educational process when using the developed methodology, which is confirmed by statistical data and positive feedback from participants in the educational process.
Optimal Range Capabilities for Low-Lift-to-Drag Ratio Mars Entry Vehicles
Authors: Engel Daniel L. , Putnam Zachary R.
Published: February 2025

Optimal solutions for maximizing the range of low-lift-to-drag ratio entry vehicles at Mars are explored. Optimal control problems are formulated to consider both vehicles using bank-angle steering as well as alpha-beta steering during entry. Both the maximum downrange and maximum crossrange problems are considered. Results are combined to determine an overall range capability and facilitate comparison to suboptimal constant bank or angle-of-attack and sideslip-angle commands. The resulting optimal control inputs often differ significantly between bank-angle steering and alpha-beta steering vehicles, the latter of which can extend range by lowering drag through sideslip-angle reversals during entry. While control over the in-plane and out-of-plane motion is found to be more decoupled for alpha-beta steering than bank-angle steering, control over the longitudinal and lateral motion is still not completely decoupled for vehicles using alpha-beta steering.
Transient Plasma Wind Tunnel Testing Under Thermomechanical Loads for Reentry Break-Up Analysis
Authors: Mueller Clemens , Leiser David , Loehle Stefan , Fasoulas Stefanos
Published: February 2025

This paper introduces a novel approach for transient plasma wind tunnel testing in an arcjet facility, enabling the experimental simulation of the aerothermal loads along reentry trajectory segments. Such experiments newly allow for the investigation of the causes of break-up events. The trajectory segment is simulated by duplicating the time-resolved profiles of the characteristic flow parameters, namely, heat flux and stagnation pressure as well as the mechanical load, which represents the aerodynamic forces. In arcjet facilities, the parameters that govern the plasma condition are split into variable and constant parameters, which define the available altitude range that can be replicated. The variable conditions arc current and ambient pressure were determined with steady-state trajectory points and traces determined between these conditions resulting in a full trajectory segment. The test time then relates directly to an altitude on the trajectory segment, which allows for an experimental determination of the main break-up altitude. The methodology is applied to a trajectory segment of the transport vehicle CYGNUS OA6, covering an altitude range from 85 to 70 km. A transient break-up experiment on an aluminum bar yielded a failure at an altitude corresponding to 77.6 km, showing a thermomechanical characteristic. These results align well with the observed break-up altitude of CYGNUS OA6, showing the potential of the proposed method.
Preliminary Design of Expendable and Reusable Mixed-Staged Launch Vehicles
Authors: Goldyn Pawel , Marwege Ansgar , Riehmer Johannes , Klevanski Josef , Gülhan Ali
Published: February 2025

One of the very first tasks in launch vehicle design is the preliminary sizing. It is necessary for further design choices, but it should deliver a precise estimate of the launch vehicle’s mass and geometry as possible. Orbital launch vehicles can be either expendable or partially/fully reusable and can assume various stage configurations. Finding an optimal solution under practical constraints is a challenging task, which gives a wide design space for potential future launch vehicles. Hence, a generalized mathematical model of a launch vehicle design has been developed and implemented as a versatile and easily modifiable programming tool for fast and parametric system characterization and optimization. The model uses several basic parameters useful in describing launch vehicles and introduces some new parameters to account for reusability. Analytical and semi-empirical correlations are used to determine the overall system and mission performance of a launch vehicle for a given reference mission, including mass and geometry, and calculate the optimal launcher staging. The implementation of the model also allows coupling with other tools, which forms a design chain with respect to aerodynamics and trajectory simulation. With this design chain, several launch vehicles have been modeled and validated, proving the applicability of the method.
Benchmarking Agility and Reconfigurability in Satellite Systems for Tropical Cyclone Monitoring
Authors: Pearl Brycen D. , Gold Logan P. , Lee Hang Woon
Published: February 2025

Tropical cyclones (TCs) are highly dynamic natural disasters that travel vast distances and occupy a large spatial scale, leading to loss of life, economic strife, and destruction of infrastructure. The severe impact of TCs makes them crucial to monitor such that the collected data contribute to forecasting their trajectory and severity, as well as the provision of information to relief agencies. Among the various methods used to monitor TCs, Earth observation satellites are the most flexible, allowing for frequent observations with a wide variety of instruments. Traditionally, satellite scheduling algorithms assume nadir-directional observations, a limitation that can be alleviated by incorporating satellite agility and constellation reconfigurability—two state-of-the-art concepts of operations (CONOPS) that extend the amount of time TCs can be observed from orbit. This paper conducts a systematic comparative analysis between both CONOPS to present the performance of each relative to baseline nadir-directional observations in monitoring TCs. A dataset of 100 historical TCs is used to provide a benchmark concerning real-world data through maximizing the number of quality observations. The results of the comparative analysis indicate that constellation reconfigurability allowing plane-change maneuvers outperforms satellite agility in the majority of TCs analyzed.
Investigation of Intake Buzz Focusing on Shock Wave Movement and Inflow/Outflow Balance
Authors: Fujii Manami , Sato Tetsuya , Taguchi Hideyuki
Published: February 2025

The intake buzz is one of the most important matters to be overcome in supersonic and hypersonic airbreathing engines. However, the buzz mechanism has not been adequately revealed yet, and further investigation is required. During the pressure-increasing period of a buzz cycle, the inflow rate exceeds the outflow rate, so the high-pressure region expands upstream inside the intake, accompanied by the upstream movement of the terminal shock wave. In this paper, the mechanism of this period was investigated numerically by changing an exit nozzle blockage to vary the outflow rate. As a result, the novel idea that the buzz phenomenon is governed by the governing equations of the moving normal shock wave as well as the mass conservation law is introduced. This is because the intake backpressure waveform and the moving velocity of the terminal shock wave are revealed to be unaffected by the outflow rate during a certain portion of the pressure-increasing period.
Probabilistic Explanations for Entropic Knowledge Extraction for Automated Satellite Component Detection
Authors: Meni Mackenzie J. , Mahendrakar Trupti , Raney Olivia D. M. , White Ryan T. , Mayo Michael L. , Pilkiewicz Kevin R.
Published: February 2025

The escalating risk of collisions and the accumulation of space debris in Low Earth Orbit (LEO) has reached critical concern due to the ever-increasing number of spacecraft. Addressing this crisis, especially in dealing with noncooperative and unidentified space debris, is of paramount importance. This paper contributes to efforts in enabling autonomous swarms of small chaser satellites for target geometry determination and safe flight-trajectory planning for proximity operations in LEO. Our research explores on-orbit use of the You Only Look Once v5 object detection model trained to detect satellite components. Although this model has shown promise, its inherent lack of interpretability hinders human understanding, a critical aspect of validating algorithms for use in safety-critical missions. To analyze the decision processes, we introduce Probabilistic Explanations for Entropic Knowledge extraction (PEEK), a method that utilizes information theoretic analysis of the latent representations within the hidden layers of the model. Through both synthetic and hardware-in-the-loop experiments, PEEK illuminates the decision-making processes of the model, helping to identify its strengths, limitations, and biases.
Wire Databases Generation Using Deep Learning Methods for Rotorcraft Wire Strike Prevention
Authors: Achour Gabriel , Harris Caleb , Payan Alexia P. , Mavris Dimitri N.
Published: February 2025

Helicopter wire strikes have been one of the most common sources of accidents in the past seven years. Poles and wires can be difficult to see for rotorcraft pilots because of their size, their location, and their blending into the background. This motivates the need to provide pilots with more tools and information about wire and pole locations. However, there is currently no comprehensive dataset summarizing the locations of poles and wires. As such, this work aims to leverage various types of data sources to generate a database of wires of interest. The proposed approach consists in first detecting pole and wire locations and then predicting a wire network. The first step combines a semantic segmentation approach applied to satellite imagery and a convolutional neural network classifier applied to street-view imagery to predict wire and pole locations. The second step applies the many-to-many Dijkstra algorithm to connect the predicted locations and generate a predicted wire map. This two-step approach is applied to a portion of Westchester County in New York, where publicly available imagery exists. Results indicate that this approach can successfully predict a wire map with high accuracy for wires alongside roads.
Expert Experience Soft Actor–Critic for Unmanned Aerial Vehicle Dynamic Target Assignment
Authors: Chen Yuxuan , Luo He , Wang Guoqiang
Published: February 2025

Deep reinforcement learning has proven highly effective in addressing sequential decision-making challenges, particularly in aerial combat involving unmanned aerial vehicles (UAVs). However, due to the prolonged decision-making process and uncertain opponent strategies in aerial combat, expert experience and manually crafted rules are often the preferred solutions. Consequently, the expert experience soft actor–critic (EESAC) algorithm is proposed to tackle the problem of dynamic target assignment for UAVs. EESAC features a customized reinforcement learning framework that includes a variable-scale reward mechanism to address the challenge of sparse rewards. Furthermore, a suppression exploration algorithm is implemented to reduce frequent target reassignments by UAVs during the initial stages, ensuring more stable and efficient mission execution. EESAC and comparator algorithms were integrated into an aerial combat simulation platform for a comprehensive evaluation. The training process and game results indicate that, compared to the comparator algorithms, EESAC significantly improves both exploration efficiency and win rate.
Four-Dimensional Aircraft Trajectory Prediction with a Generative Deep Learning and Clustering Approach
Authors: Zhang Haoyuan , Liu Zhizhao
Published: February 2025

Medium- and long-term four-dimensional (4D) aircraft trajectory prediction (TP) is a critical technology in air traffic management (ATM). This paper addresses the issue of existing medium- and long-term TP methods that are difficult to accurately fit aircraft trajectory data distributions. We propose a 4D TP method based on K-medoids clustering and conditional tabular generative adversarial networks (CTGAN), called C-CTGAN. Comparative experiments with four long short-term memory (LSTM)-based models and the original CTGAN model show that the proposed model’s TP accuracy is significantly higher than others when predicting medium- and long-term trajectories. When using the trajectory datasets without holding and a prediction time span of 10 min, compared to the convolutional neural network (CNN)-LSTM model, the C-CTGAN model reduces the mean absolute errors (MAEs) of core trajectory parameters, such as latitude, longitude, geometric altitude, and ground speed, by 69.89, 15.00, 74.07, and 84.21%, respectively. Compared to the original CTGAN model, the MAE is reduced by 20.43, 39.09, 31.98, and 17.07%, respectively. When using the trajectory datasets with holding, compared to the CNN-LSTM model, the C-CTGAN model shows MAE reductions of 14.08, 23.68, 31.46, and 2.86%, respectively. Compared to the original CTGAN, the reduction is 34.88, 2.69, 23.16, and 73.91%, respectively.
Performance Analysis of Three Predictors for Mitigating Input and Output Time Delays
Authors: Sakib Nazmus , Ahmed Zakia , Woolsey Craig A.
Published: February 2025

This paper presents a novel extended Kalman filter (EKF)-based nonlinear predictor—the extended Kalman predictor (EKP)—and compares its performance with two linear predictors, the Smith predictor (SP) and the Kalman predictor (KP). A motivating application is telerobotic operation using a predictive display that requires knowledge of the robot pose despite time delays at the input and the output. The paper provides the mathematical formulation of the EKP, as well as the two linear predictors, and demonstrates their use for the simulated flight of a small, fixed-wing uncrewed air vehicle. The EKP performs comparably to the KP when the aircraft motion experiences small perturbations from a nominal trajectory, but the EKP outperforms the KP for larger excursions. The SP performs poorly in every case.
Multi-Agent Grouping and Routing with Cooperative Tasks
Authors: Choi Euihyeon , Ahn Jaemyung
Published: February 2025

This paper introduces a grouping and routing problem of multiple agents for cooperative missions. The introduced problem, referred to as the Vehicle Grouping and Routing Problem with Profits, aims to maximize the total reward obtained by conducting a multi-agent mission (e.g., cooperative reconnaissance) while reducing its makespan by appropriately grouping the agents and determining their routes under operational constraints (e.g., fuel, endurance). A mixed-integer linear programming formulation and a conservative column generation-based solution procedure for the problem are proposed. A case study with homogeneous and heterogeneous agents and numerical experiments involving a cooperative reconnaissance mission with multiple unmanned aerial vehicles demonstrate the validity of the proposed formulation and solution procedure.
HabSim: A Modular-Coupled Virtual Testbed for Simulating Extraterrestrial Habitat Systems
Authors: Azimi Mohsen , Lund Alana , Fu Yuguang , Montoya Herta , Vaccino Luca , Murali Krishnan R. , Rhee Seungho , Chebbo Leila , Shahriar Adnan , Wang Zixin , Maghareh Amin , Dyke Shirley J.
Published: February 2025

Extraterrestrial habitats involve a tightly coupled combination of hardware, software, and humans while operating in an unforgiving environment that poses many risks, both anticipated and unanticipated. Traditional approaches with such systems of systems focus on reliability, robustness, and redundancy. These approaches seek to avoid failure rather than reduce overall risk. However, faults are inevitable, and understanding and managing the complex and emergent behavior and cascading events of such a complex system is critical. This study describes the development of HabSim, a computational simulation environment intended to support research to establish the know-how to design and operate resilient and autonomous SmartHabs. HabSim is a modular virtual testbed composed of many of the coupled dynamic systems expected in a typical SmartHab. A heterogeneous set of interconnected physics-based and phenomenological models is used to represent the essential functions of a SmartHab. HabSim further considers disruptions and models damage and repair of certain components. This paper discusses a) system and subsystem requirements of the deep space habitat included in the HabSim platform; b) architectural choices made in response to the requirements; c) technical considerations for developing, verifying, configuring, and executing HabSim; and d) illustrative sample results from a simulation of a representative disruption scenario.
Monolithic p-Adaptive High-Order Aerodynamic Shape Optimization
Authors: Coppeans Alexander W. C. , Fidkowski Krzysztof J. , Martins Joaquim R. R. A.
Published: February 2025

Aerodynamic shape optimization requires a robust, accurate, and efficient flow solver. However, during aerodynamic shape optimization, large geometry and flow solution changes may decrease solution accuracy and efficiency on fixed meshes. The optimizer may converge to a spurious optimum if the solution loses accuracy. We use the discontinuous Galerkin (DG) method to tackle this problem because it yields high-order-accurate solutions that often have less error per degree of freedom compared to second-order finite-volume methods. Because DG degrees of freedom often incur a higher computational cost, we take advantage of local adaptation to maximize accuracy at a given cost. However, during optimization, it is not clear when to adapt to avoid overoptimizing initial designs and to avoid errors polluting the optimal solution. We develop an adaptation strategy that reaches a target error at the end of a single optimization loop. Finally, we present results for two airfoil optimization test cases. Our results show that this adaptation procedure outperforms optimization using fixed-fidelity DG and second-order finite volume on a per-degree-of-freedom basis.
Simultaneous Design and Trajectory Optimization Strategies for Computationally Expensive Models
Authors: Kaneko Shugo , Martins Joaquim R. R. A.
Published: February 2025

Simultaneous design and trajectory optimization aims to find the best possible design of a dynamic engineering system, such as an aircraft, by considering the coupling between a physical system design and its trajectory. Multidisciplinary design optimization (MDO) fully considers this coupling and corresponding design trade-offs. This article discusses the computational efficiency of MDO formulations for design-trajectory optimization. Numerical studies are performed to compare two monolithic MDO architectures and two design-trajectory coupling strategies on aircraft design test problems. The test problems concurrently optimize a climb trajectory, wing design based on a low-fidelity aerostructural analysis, and aircraft sizing variables. The results indicate that surrogate-based coupling is more efficient than direct coupling when there are only a few variables coupling the trajectory and disciplinary models, whereas direct coupling is preferable otherwise. The simultaneous analysis and design (SAND) architecture outperforms the multidisciplinary feasible (MDF) architecture when using direct coupling, whereas the costs of SAND and MDF are comparable with surrogate-based coupling. The results and discussion in this paper provide general guidelines for selecting a computationally efficient approach for simultaneous design and trajectory optimization.
Estimation of the Parameters of a Three-Dimensional Gust Model with a Wind Lidar
Authors: Musso Christian , Boulant Thibault , Valla Matthieu , Lefebvre Sidonie , Michel David T.
Published: February 2025

Reducing fuel consumption for future airplanes is a critical issue. One solution is to design airplanes with a large wing aspect ratio to increase the lift. However, such wings are sensitive to loads induced by gusts. A technique consists of using adaptive wings that modify their shape according to the gust measured ahead of the airplane (the so-called feed-forward gust load alleviation). The gust is typically measured using a wind lidar at the nose of the airplane. To determine the three-dimensional wind field, the lidar is addressed along different axes to obtain the projections of the wind along each of them. In this paper, we present a methodology for reconstructing a gust immersed in wind turbulence from the lidar measurements. The proposed estimation methods are based on the Bayesian filtering theory. Considering simplified models, numerical simulations show the feasibility of such a reconstruction.
Lattice Boltzmann Formulation for Eight-Wave Magnetohydrodynamics
Authors: Dellar Paul J.
Published: February 2025

Magnetohydrodynamics couples the Navier–Stokes and Maxwell equations to describes flows in electrically conducting fluids. The divergence of the magnetic field must vanish, but numerical algorithms typically do not preserve this condition exactly. Artifacts can then arise in solutions, such as spurious forces parallel to the magnetic field. These artifacts can be alleviated by using extended sets of Maxwell’s equations that include magnetic charges and currents and hence are invariant under duality rotations that interchange the electric and magnetic fields. The eight-wave formulation supposes that the magnetic current arises from magnetic charges being advected by the fluid. The magnetohydrodynamic equations are then Galilean invariant even when the divergence of the magnetic field is nonzero. The evolution equation for the magnetic field then resembles Jeffery’s equation that describes the orientations of a suspension of axisymmetric particles. The ideal electric field is invariant under the extra terms proportional to the divergence of the magnetic field. This property leads to particularly simple lattice Boltzmann formulations for two of the three variants, with different treatments of the momentum equation, that are constructed and compared. The formulation that implements the Lorentz force directly, rather than via the Maxwell stress, proves more stable in numerical experiments.
Data-Driven Full-Field Prediction of Rotorcraft Fuselage Using Measurable Acceleration Response
Authors: Kim Hyeongmo , Kim Hyejin , Jeong Inho , Kang Woo-Ram , Lee Hakjin , Cho Haeseong
Published: February 2025

This paper presents a study aimed at predicting the full-field acceleration response of a rotorcraft fuselage. The prediction was achieved from the acceleration response observed at a limited sensor location on the rotorcraft. Moreover, the prediction was realized through a framework that used a data-driven model order reduction and long-short-term memory artificial neural network. To validate the performance of the proposed framework, a rotor/fuselage one-way coupled analysis was performed by considering a fuselage with a utility helicopter configuration and a platform rotorcraft. As a result, the efficiency and accuracy of the full-field prediction performance were confirmed by comparing with the finite element solutions.
Foreign Object Impact Analysis–Assisted Certification Studies for On-Demand Mobility Aircraft
Authors: Vaghela Pradeep , Raza Hasan , Stumpf Eike , Bayandor Javid
Published: February 2025

Aircraft are prone to foreign object damage, particularly bird strikes during takeoff and landing. Modern air taxis are expected to make more frequent stops to serve as viable competition to the current urban transportation system. To ensure safety, all passenger aircraft must meet crashworthiness regulations against foreign object damage such as bird strikes and drone impacts. Given the heightened frequency of stops in urban settings and operating altitudes below 10,000 feet, air taxis are particularly prone to such impacts. This study uses finite element methods to investigate the forces resulting from direct impacts on an on-demand air mobility service aircraft. A bird surrogate, modeled using discrete particles, and a quadcopter drone are used as projectiles. Impact analyses are performed on the canopy, fuselage, and wing of the aircraft. Resulting stresses, displacements, dynamic forces, and energy transfer from the soft and solid body impacts are compared with each other to investigate the post-impact behavior of the aircraft structures.
Adaptive Physics-Informed Neural Network Based Directional Sampling Method for Efficient Reliability Analysis
Authors: Yan Yuhua , Lu Zhenzhou
Published: February 2025

To efficiently estimate the failure probability for structures with performance function governed by the partial differential equation, this paper proposed an adaptive physics-informed neural network based directional sampling (A-PINN-DS) method. The proposed A-PINN-DS possesses both the low dependence on labeled data from PINN and the high failure domain exploring efficiency from DS. In the proposed method, DS is firstly employed to generate the random input target collocation sample pool (TCSP) with high failure domain exploring efficiency. Then in TCSP, the neural network is trained by the partial differential physics information governing the performance function, and the neural network trained to be convergent in TCSP is used to predict the performance function response of TCSP, on which the failure probability can be estimated by DS. Because the proposed method only uses partial differential physics information instead of finite element simulation to train neural network in the TCSP for predicting performance function, it remarkably reduces the computational cost for estimating failure probability. To improve the efficiency of training PINN in TCSP, this paper designs a strategy of adaptively updating loss weights and a convergence distinguishing strategy for training PINN. Finally, the feasibility and superiority of the proposed method are verified by several examples.
Hybrid Finite-Difference Physics-Informed Neural Networks Partial Differential Equation Solver for Complex Geometries
Authors: Xiang Zixue , Peng Wei , Yao Wen , Zhou Weien
Published: February 2025

The physics-informed neural network (PINN) is effective in solving the partial differential equation (PDE) by capturing the physics constraints as a part of the training loss function through the automatic differentiation (AD). This study proposes the hybrid finite difference with PINN (HFD-PINN) to fully use the domain knowledge. The main idea is to use the finite-difference method (FDM) locally instead of AD in the framework of PINN. We use AD at complex boundaries and FDM in other domains. To avoid the background mesh, we propose HFD-PINN-sdf, which uses the signed distance function (sdf) to avoid the difference scheme from crossing the domain boundary. In this paper, we demonstrate the performance and compare the results with different numbers of collocation points and architectures for the Poisson equation and Burgers equation. We also chose several different finite-difference schemes, including the compact finite-difference and Crank–Nicolson methods, to verify the robustness of HFD-PINN. We take the heat conduction problem and the heat transfer problem on the irregular domain as examples to demonstrate the efficacy. In summary, HFD-PINN is more instructive and efficient when solving PDEs in complex geometries.
Multidetector Computed Tomographic Imaging of the Mixed Total Anomalous Pulmonary Venous Drainage
Authors: Singh Ajmer , Joshi Swati
Published: February 2025

A 1-month-old infant with worsening respiratory distress and cyanosis was found to have a combination of cardiac and supracardiac, i.e., mixed total anomalous pulmonary venous drainage (TAPVD) or as it is called a type IV TAPVD. Multidetector computed tomographic imaging was done to corroborate the diagnosis and it provided precise anatomic information and correct pre-operative diagnosis for pre-surgical planning. A brief description case is described.
Гидроэлектродинамический эффект в КНЧ-диапазоне на береговой линии оз. Байкал
Authors: Башкуев Ю.Б. , Аюров Д.Б. , Шунков А.Д.
Published: February 2025

В статье рассмотрен гидроэлектродинамический эффект в КНЧ-диапазоне на береговой линии озера Байкал. Вследствие движения набегающих волн на песчаный берег возникает фильтрационное поле, относящееся к электрокинетическим явлениям. Представлена аппаратура и методика проведения работ, схема установки измерительных электродов. Проведён анализ временных процессов и их амплитудных спектров. Дана интерпретация полученных результатов.

Introduction. As incoming waves traverse the sandy shoreline, they give rise to a filtration field linked to electrokinetic phenomena. The porous nature of the sand forms a network of capillaries facilitating fluid flow. This, in turn, leads to the development of a double electrical layer at the interface of the liquid and solid phases. Charges get adsorbed on the capillary walls, while others are carried away by the moving fluid flow, causing a redistribution of charges and the emergence of an electric field. For the measurement of such fields in electrical prospecting, the study introduces the use of the natural field method. In contrast to the conventional approach employing only two electrodes, this study employs a multi-channel setup with six electrodes. This setup, with synchronous recording on all channels, enables the determination of the spatiotemporal characteristics of the incident waves. Specifically, it allows the calculation of the average speed of the oncoming wave as it approaches the shore. The aimof this study was to analyze measurements of the hydroelectrodynamic effect in the ELF range on the lake shoreline and interpret the results obtained using the proposed equipment and experimental techniques. The scientific and practical significance is exhibited in the exploration of hydroelectrodynamic fields arising when waves approach the lake shoreline. The novelty of the work lies in the fact that, for the first time, these fields were recorded on the shores of the vast freshwater Lake Baikal. Findings.The paper introduces a method for observing the hydroelectrodynamic effect along the coastline of Lake Baikal. It discusses the equipment and methodology used for conducting full-scale experiments. The paper includes an analysis of time processes and their amplitude spectra. Assessment of the obtained amplitude spectra indicates that hydroelectrodynamic fields range from ten thousandths of a hertz to a few hertz, with a significant concentration of energy occurring at frequencies up to 0.5 Hz, suggesting an ELF nature of the resulting electric fields. Additionally, a single electrode was employed to examine the process of water movement toward the shore and back. The onrush process is characterized by a relatively rapid increase in voltage, with an average amplitude reaching up to 20 mV. The drainage process takes longer due to water draining under the influence of gravity and being retained by sandy soil.
The distribution of groundwater uranium in Chintamani village, Karnataka, India
Authors: Rampur Sadashiva , Kumar V. K. Mahesh , Pelli Pavan R. , Sarkar Senjuti , Pramanik Samayeta , Majumdar Upama , S. Shravanthi , Meenakshi Bhavana , G. Santhanakrishnan Srinidhi , Pendem Rushi , Ghosh Tanushree , Nagarajan Deepesh
Published: February 2025

Chintamani village, Chikkaballapura district, Karnataka, India was found to possess high aquifer uranium concentrations. Geologically, Chintamani village is located on bedrock that is rich in elements like potassium (K) that naturally contain high levels of radioactive elements, such as uranium and thorium, due to the presence of alkali-feldspar granites and gneisses. Aquifer depletion has caused the concentration of these elements in groundwater to increase over time, posing a potential health hazard to the residents of Chintamani village. Here, we report the sampling of groundwater from 12 borewells located in Chintamani village in between the period of August 2024 to December 2024. We observed groundwater uranium concentrations of 0.02 ppm to 8.64 ppm. Data for borewell depth, the quantity of total dissolved solids (TDS), and the elemental composition of TDS is also reported. We observed a statistically significant spatial distribution of uranium concentrations in Chintamani village. Borewells possessing the highest observed concentrations of uranium were clustered towards the northwestern region of the village. This dataset is expected to serve as a resource for guiding potential remediation efforts in these locations.
Data-driven recursive kinetic modeling for chemical reactions
Authors: Hua Tian-Wei , Huang Gui-Xiang , Qian Chen , Zeng Hou-Wei , Jiang Jun , Yu Han-Qing
Published: February 2025

Kinetic models are crucial for analyzing reaction mechanisms and optimizing conditions. However, traditional models suffer from limitations such as lack of accuracy, narrow applicability, and difficulty in handling complex reaction conditions. Here, we develop a data-driven kinetic model with recursive algorithm and a multiple estimation strategy to predict chemical reaction kinetics. The model establishes recursive relationships between the concentrations of reactants or products at different times, rather than traditional concentration-time equations, to describe the kinetic patterns. It demonstrates superior accuracy, broad application scope, robustness, and few-shot learning capability on a simulated dataset including 18 chemical reaction types. Furthermore, its applicability to real-world chemical reactions is confirmed on the datasets of three practical reactions with complex kinetics. In addition, its advantages over traditional models were summarized through comprehensive comparison. This work introduces a high-performance kinetic model, offering a potential to accelerate chemical research via advanced kinetic analysis.
Synthesis of an ultra-bright rotaxane with threaded BODIPY stoppers
Authors: Hicguet Matthieu , Mongin Olivier , Berrée Fabienne , Trolez Yann
Published: February 2025

Two new boron-assembled rotaxanes were successfully synthesized. One of them possesses two stoppers of a new kind consisting of threaded BODIPYs. Its precursor bearing three boron atoms is non fluorescent. To release the macrocycle, the selective removal of one boron out of the three was achieved in high yield using potassium hydroxide. The removal of this boron triggers the fluorescence of the system, making this rotaxane highly fluorescent, with a fluorescence quantum yield of 64%. Combined with a high absorption coefficient, this rotaxane is one of the brightest reported so far with a brightness of 1.24 x 105 mol-1.L.cm-1.
Retraction Note:Professional integration of teachers through the many aspects of socialisation at work using ISaTE as a measurement tool
Authors: Napoleon Arrey Mbayong  , Stephen Mokondo Moki
Published: February 2025

The Original Article was published on 24 December 2024
The Editor in Chief has retracted this article after concerns were raised about published article. 
The article titled: “Professional integration of teachers through the many aspects of socialisation at work using ISaTE as a measurement tool” by Napoleon Arrey Mbayonga and Stephen Mokondo Mokia, published in Journal of Management and Science (Vol. 14, No. 4, 2024, pp. 7-24) Available here: https://www.jmseleyon.com/index.php/jms/article/view/794 is an exact plagiarism of an article published in journal in 2020:“L’insertion professionnelle des enseignants au travers des multiples aspects de la socialisation au travail : l’ISaTE, un instrument de mesure pour les appréhender” by  Coppe et al., published in Mesure et Évaluation en Éducation (Vol. 43, No. 3, 2020, pp. 67-102) (DOI: https://doi.org/10.7202/1083008ar).
After a thorough analysis of both texts, it is evident that the article by Napoleon Arrey Mbayonga and Stephen Mokondo Mokia,is an almost identical reproduction of the original work, with only minor modifications such as changes in authorship and superficial rewording. The entire structure, content, references, and results have been copied without proper attribution to the legitimate authors.
The Editor-in-Chief no longer has confidence in the reliability of the data reported. The authors did not respond to correspondence from the publisher about this retraction.
Publisher’s Note: Eleyon Publishers remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
APLICACIÓN DE REDES NEURONALES PARA EVALUAR HABILIDADES GERENCIALES EN LA FORMACIÓN DE ADMINISTRADORES
Authors: Tiburcio Maria de Lourdes , Marcano Annherys Isabel Paz , López Roberto Godinez , Montero Eva Lozano
Published: February 2025

Objetivo: El objetivo de este estudio es investigar la aplicación de las redes neuronales para identificar y evaluar habilidades gerenciales y competencias clave mediante un modelo de aprendizaje supervisado en estudiantes de la región Laja-Bajío, México.
 
Marco Teórico: El uso de redes neuronales artificiales (RNA) como herramienta para analizar habilidades y competencias gerenciales en estudiantes de administración. Las RNA, inspiradas en la neurobiología, permiten procesar datos complejos y realizar predicciones, siendo útiles en campos como las ciencias sociales.
 
Método: La metodología adoptada para esta investigación comprende un enfoque cuantitativo con técnicas de estadística descriptiva e inferencial, aplicando el modelo perceptrón de las RNA, la recolección de datos se realizó utilizando encuestas aplicadas a 360 estudiantes analizadas con SPPSS versión 27.
 
Resultados y Discusión: Los resultados obtenidos revelaron que las RNA son efectivas para analizar datos multidimensionales y prever competencias necesarias para el mercado laboral actual. Se destaca la importancia de las habilidades humanas y las competencias interpersonales como factores críticos.
 
Implicaciones de la Investigación: El estudio concluye que las RNA son herramientas flexibles y potentes que pueden mejorar la formación académica en administración. Sugiere su implementación para fortalecer currículos y preparar a futuros gerentes frente a las demandas organizacionales contemporáneas.
 
Originalidad/Valor: Este estudio contribuye a la literatura al uso de redes neuronales artificiales (RNA) como herramienta para analizar habilidades y competencias gerenciales en estudiantes de administración. Las RNA pueden ser una herramienta de gran valor para realizar predicciones en el campo de las ciencias sociales y administrativas.
In-Country Free Trade Zone in Post–Conflict Aceh: Illegal Cigarette Trade in Sabang, Indonesia
Authors: Lhena Darwin Rizkika , Akmal Saiful , Nur Zalikha Siti , Ahsan Abdillah , Thalal Muhammad
Published: February 2025

The implementation of the Sabang Free-Trade Zone (FTZ) has implications for the increasing distribution of illegal cigarettes in the mainland areas of Aceh. It exacerbates state financial losses, community health problems, and the workload on customs to conduct control and supervision. This qualitative study aims to explore how the Free-Trade Zone in Sabang was managed as an instrument for political concession in the Aceh conflict and its quota decision mechanism on illegal cigarettes. Using a grounded qualitative research design, we conducted 12 in-depth interviews with key stakeholders. Four important findings are reflected in this study. First, the management of the Sabang-Free Trade Zone is highly influenced by political aspects and a lack of managerial competence. Second, there is a dilemmatic perspective of the conflicting parties regarding the Sabang FTZ. Third, the quota mechanism related to the distribution of imported cigarettes is not regulated and merely relies on importers’ requests. Lastly, the control and supervision system at the Sabang FTZ is weak. These findings are expected to serve as the foundation for policy recommendations and lessons on the illegal cigarette trade in Indonesia and other post-conflict countries, as well as free trade zones in neighbouring countries like Malaysia, Thailand, Singapore, and the Philippines.
The Effect of Perceived Spiritual Leadership on Organizational Agility: A Field Study
Authors: Fettahlıoğlu Ömer Okan , Döngül Esra Sipahi , Hamid Nur
Published: February 2025

The current scenario compels businesses to adopt an agile structure to navigate unprecedented changes and to help employees adapt effectively. This study was conducted to support the hypothesis that spiritual leaders can guide employees in adapting to changes and enhancing organizational agility. Spiritual leadership can improve organizational agility by increasing employees’ trust and commitment, making it easier for them to adjust to change. Data were collected from 405 employees in both top- and bottom-level positions within the manufacturing industry in the Malatya and Kayseri provinces of Turkey. This quantitative research model was developed and tested using correlation and regression modeling techniques. The findings revealed a significant relationship and interaction between spiritual leadership and organizational agility (r = 303; and r = 504, p < 0.05)] (R 2: 028; p: 001. Business agility is achieved through adaptation to change, which necessitates that employees also adapt effectively to these changes.
Utilizing Digital Media for Guidance and Counseling in Education
Authors: Suryawati Citra Tectona , Susilo Agus Tri , Asrowi Asrowi , Surur Naharus
Published: February 2025

This causal correlational study aims to find out the effect of factors of digital technology on guidance and counseling teachers’ usage of guidance and counseling media. It involved eighty-five guidance and counseling teachers in seven regions, recruited using a convenience sampling technique. Data were garnered using the Attitude scale for digital technology developed by Emine [1], which has been considered valid and highly reliable (1.000). Data were analyzed using a linear regression test and path analysis using SPSS. The effect size of these factors varied, with the highest score observed in “technology for me” (75.1%), followed by interest in technology (70.3%), technological use (63.9%), competence (59.6%), social network (54.2%), conscious use (53.7%), recreational use (43.2%), and negative aspects (25.2%). These factors exhibited significant correlations with and influenced the usage of guidance and counseling media among guidance and counseling teachers in this study. Consequently, it is necessary to implement interventions aimed at enhancing the utilization of digital technology for guidance and counseling services.