bluuebunny/crossref_metadata_2025_split huggingface dataset:
Studying the Large Span Multi-Cell Steel Box Girder – An Engineering Mechanics Look
Authors: Duong Tham Hong 
Published: February 2025

Abstract
Thin-walled closed steel structures are now applied widely in urban regions, especially in metropolitan or megacities. Several large span overheads, fly-overs, overpasses, and city sky bridges are built; some are horizontally curved structures for aesthetic, economic, and effective purposes. The working conditions for such structures require careful analysis, not only in the structural analysis but in the science of materials with different levels of knowledge. Stress-strain relationships in static and dynamic aspects, relating to stiffness, local and overall buckling, etc., are primary issues in engineering mechanics. Firstly, it is necessary to review the response of the thin-walled structures subjected to torsion, including equations of internal forces and moments, as well as both flexural and torsional moments of horizontally curved structures. Secondly, it focuses on studying the behavior of the thin-walled structures subjected to flexion and torsion. Finally, some in-depth investigations into warping effects are tentatively made. Some comparisons between the analytical and numerical results of normal stresses indicate a consistency of about 70% to 77% between the two solutions. Furthermore, stresses and strains at corner points of the cross-section result in distortional warping effects. Besides, by conducting a modal analysis, based on the modal participating mass, results indicate that lateral and torsional vibrations dominate in the first two modes of curved structures, as well as the straight structures. Furthermore, the sharper curvature is, that the torsional vibration appears in the first mode, disregarding the condition of supports. These contribute more to previous understandings of this special structure and unusual secondary effect _ ’warping’. The article will only focus on the superstructures in the hope of clarifying the working conditions and responses of the HCB in a general look at engineering mechanics; any infrastructure analysis is limited.
Ride Comfort Evaluation of an Motorbike with Random Excitation by a Multi Body Dynamic Model
Authors: Pham Ngoc Dai , Tran Huu Nhan , Tran Duc , Nguyen Dinh Hung 
Published: February 2025

Abstract
An motorbike is designed with full technical specifications regarding size and weight distributed on the front and rear axles of the vehicle. The wheel is connected to the vehicle body frame through a suspension system including linkage, spring, and shock absorber elements. The designed suspension system specifications play a very important role in ensuring the vehicle’s ride comfort, safety and road holding ability. To ensure technical requirements, the suspension system is designed with the spring and damper parameters selected as reality. The ride comfort greatly affects the quality of the vehicle’s design and the health safety of people using the vehicle. This paper focuses on the ride comfort of an electric motorbike. The assessment of ride comfort is analyzed by a Multi-Body Dynamic (MBD) model with 4 degrees of freedom (4DOF) subjected under the random excitation, according to ISO 8608 standard. The simulation is performed with three random types of road profile, class A, class B, class C. The velocity is in the range of from 10 ÷ 80 (km/h), at each value of velocity the Root Mean Square (RMS) index of the acceleration in the time domain is determined. The acceleration index includes to frequency weighting according to ISO 2631:1-1997 standard is used to evaluate the ride comfort. The MBD model in 3-dimensional (3D), including wheels in contact with the road surface, linkage bars and suspension systems linked to the vehicle frame through linkage joints, is employed. The obtained results show that, with the same v value, when the vehicle moves on road surface A class, the ride comfort is always smaller than road surface B class and C class. Considering the same type of road surface, as v increases, the ride comfort index increases, leading to a decrease in comfort and an increase in suspension working space requirement.
Elastic Model for Polyethylene Terephthalate Fibre Reinforcement Structures: Application in Free Vibration Analysis of FG-TPMS Shell Panels in Concrete (PET-FG-TPMS)
Authors: Duong Thoi V. , Nguyen Khuong D. 
Published: February 2025

Abstract
This paper investigates new frameworks for Polyethylene Terephthalate fiber-reinforced functionally graded triply periodic minimal surface shells (PET-FG-TPMS) with concrete material. We propose one functional classification framework focused on controlling mass density, elastic modulus, and shear modulus, with an average porosity of 0.35. The study examines three plate-based TPMS structures: Primitive, Gyroid, and I-Wrapped Package-graph. Free vibration analyses of the plates and shell are performed using a theoretical model with three-dimensional isogeometric analysis (3D IGA). Critical parameters like porosity coefficient, TPMS type, inclusion types, and volumes of the two material phases are thoroughly explored. Their effects on the plate response are presented for different thicknesses. The mass density framework is particularly promising for comparing different TPMS structures, with the TPMS compensating for the stiffness deficit of PET reinforcement, as assessed through fundamental vibration frequencies. Each type of TPMS has its advantages with different PET reinforcement ratios. This study aims to advance the development of concrete PET-FG-TPMS plates and shells, highlight the impact of various functional classification frameworks, and guide the design of lightweight, mechanically efficient structures.
The development of mortar method for the non-conforming multi-patch elastic problems in isogeometric analysis
Authors: Vo-Manh Quynh , Hoang Cong Huu , Nguyen Khuong D. 
Published: February 2025

Abstract
Isogeometric Analysis (IGA) leverages Non-Uniform Rational B-Splines (NURBS) for complex geometries, offering an attractive alternative to traditional Finite Element Analysis (FEA). However, connecting NURBS patches in IGA often requires non-conforming interfaces. The Mortar method addresses this challenge by efficiently coupling such interfaces in solving Partial Differential Equations (PDEs). This work presents a novel development of the Mortar method tailored explicitly for non-conforming multi-patch elastic problems in IGA. We introduce a novel formulation for the coupling coefficient within the Mortar method, ensuring accurate solution transfer across non-matching interfaces. The efficient implementation of this method in the IGA framework is also presented. The effectiveness of the proposed method is demonstrated through numerical examples, showcasing its ability to handle complex geometries with significant computational speedup compared to conforming patches. Validation is performed using established benchmark problems in linear elasticity. Finally, we discuss the advantages and limitations of the proposed Mortar method, highlighting its potential for practical engineering applications. We also identify promising avenues for future research in this area. This work contributes significantly to developing robust IGA techniques for complex engineering problems involving multi-patch domains. It provides a valuable resource for researchers and practitioners seeking efficient solutions for elastic analysis using IGA.
Vibration analysis of shaft generator driven from main engine
Authors: Le-Dinh Tuan , Tran Hai 
Published: February 2025

Abstract
In recent years, offshore service vessels have increasingly used hybrid propulsion systems with generators mounted coaxially with the main engine. These latest state-of-the-art shaft generators enable ship operators and builders to benefit from efficiency, performance, and reliability. By reducing a ship’s CO2 emissions, it also helps ships meet the International Maritime Organization’s (IMO) EEDI (Energy Efficiency Design Index) measure targeting new ship designs and construction to ensure energy-efficient standards and EEXI (Existing Ship Energy Efficiency Index) measure addressing existing ships and promotes retrofits and optimizations. The paper presents the vibration analysis of Power Take Off generators (PTO) driven by engine-driven reduction gear. This analysis relates measurements of vibration carried out at 90% and 100% rated generator speed with unloaded generator and ship service speed under steady state operation. First, the study introduced experimental measurement on the same type of PTO generator installed on different ships with the same or different main engines. Second, based on this experimental measurement, the vibration analyses are evaluated and compared to relevant criteria and standards. The research results of the vibration analysis and the comparison with the criteria required on these in-shaft generators driven from the main engine were used as results of the quality assessment of the installation of hybrid propulsion systems for recent new building ships in Vietnam. This was verified by the results of vibration measurement, analysis and evaluation on shaft generators installed on three recent new-building ships.
IoT-based Smart Agriculture System: Design of Farming Diary
Authors: Nguyen-Tat Thien B. , Phuc Kha Ninh Nguyen , Do Tri Nhut 
Published: February 2025

Abstract
Agriculture has played an important role in human society since ancient times, providing livelihoods and contributing signi(icantly to the economy of a country. Nowadays, climate change is increasingly having a direct and profound impact on crop productivity. These changes affect soil nutrients, pests, and water levels. To mitigate these impacts and increase crop productivity, IoT (internet of things) technology has been and is being utilized to transform agricultural cultivation processes not only to improve production methods, and reduce costs but also to ensure traceability and enhance environmental sustainability. In this paper, a smart farming diary is designed and implemented on mobile and web applications based on IoT technology. The system allows farmers to record detailed farming activities, including information on seeds, fertilizers, pesticides, weather, and other factors affecting crops. All data is collected from sensors, and IoT terminal devices for statistics, stored as logs, and analyzed to evaluate the effectiveness of the system.
A system for detecting scratches on the surface of small-sized metal shafts after the grinding process using optical techniques combined with computer vision.
Authors: Dau Sy Hieu , Nguyen An Khang Le , Thi Phuc Dang 
Published: February 2025

Abstract
During the grinding process of metal machine parts requiring a high degree of smoothness, the use of diamond-surfaced grinding tools, specialized grinding stones, or high-hardness metals are common choices. However, during grinding, surface tool damage or misalignment between grinding surfaces can cause defects such as cracks, scratches, or complete surface destruction. Detecting small scratches is one of the biggest challenges due to their size and distribution, making it difficult to quickly identify them using the human eye. Automated systems, on the other hand, struggle to highlight scratches because automatic optical lighting systems face strong reflections from the metal surface, especially cylindrical surfaces after being polished. As a result, the images obtained lack controlled reflection positions and contrast between normal and scratched areas, leading to inefficiency in detecting these scratches. In this study, we propose an optical system combined with lighting techniques to highlight scratches on the surface of a cylindrical machine part after polishing, thereby detecting and classifying these defects to make pass-fail decisions in practical production line applications.
Exploring The Efficiencies Of Bi-LSTM Model and Attention Mechanism In Solar Power Forecasting
Authors: Minh Le Thi Tinh , Tri Si Ngo , Truc Nguyen Thi Kim 
Published: February 2025

Abstract
Solar energy, as a pivotal renewable resource, holds the potential to address global energy demands while mitigating the environmental impact of traditional energy sources. Accurate forecasting of solar energy output is essential for efficient power system management, ensuring grid stability, and facilitating informed decision-making in energy markets. Recent research has highlighted the integration of attention mechanisms into Long Short-Term Memory (LSTM) models, demonstrating their superior predictive capabilities in this domain. This study contributes to the field by exploring a Bidirectional LSTM (BiLSTM) model augmented with an attention mechanism (BiLSTM-Attn), incorporating three time-series features for enhanced solar energy forecasting. The proposed predictive model is empirically compared to multi-variable time series models, revealing the efficiencies of the BiLSTM-Attn. The results are extensively evaluated on real solar power datasets in Vietnam and overseas.
Multilayer perceptron approach for determining the centroid position of the electromagnetic shower in laterally segmented calorimeter
Authors: Hamdi W. , Mazouz M. , Chaibi S. 
Published: February 2025

Abstract
This paper presents a method employing a Multi-Layer
Perceptron (MLP) neural network to enhance the spatial resolution of
laterally segmented electromagnetic calorimeters. The study, based
on GEANT4 simulations, explores the impact of different MLP
architectures and hyperparameters on spatial resolution across a
range of calorimeter block sizes and incident photon energies from
1 GeV to 10 GeV. Optimal configurations are identified,
including the number of input neurons, hidden layers, and neurons
per layer. The optimized MLP model consistently outperforms the
widely used center of gravity method, achieving a significant
improvement in spatial resolution that ranges from 8% for 1 GeV
photons and a block size of half the Molière radius to 22% for
10 GeV photons and a block size of twice the Molière radius.
Flapping dynamics and wing flexibility enhance odor detection in blue bottle flies
Authors: Haider Naeem , Lou Zhipeng , Hsu Shih-Jung , Cheng Bo , Li Chengyu 
Published: February 2025

Abstract
One of the most ancient and evolutionarily conserved behaviors in the animal kingdom involves utilizing wind-borne odor plumes to track essential elements such as food, mates, and predators. Insects, particularly flies, demonstrate a remarkable proficiency in this behavior, efficiently processing complex odor information encompassing concentrations, direction, and speed through their olfactory system, thereby facilitating effective odor-guided navigation. Recent years have witnessed substantial research explaining the impact of wing flexibility and kinematics on the aerodynamics and flow field physics governing the flight of insects. However, the relationship between the flow field and olfactory functions remains largely unexplored, presenting an attractive frontier with numerous intriguing questions. One such question pertains to whether flies intentionally manipulate the flow field around their antennae using their wing structure and kinematics to augment their olfactory capabilities. To address this question, we first reconstructed the wing kinematics based on high-speed video recordings of wing surface deformation. Subsequently, we simulated the unsteady flow field and odorant transport during the forward flight of blue bottle flies (Calliphora vomitoria) by solving the Navier–Stokes equations and odorant advection-diffusion equations using an in-house computational fluid dynamics (CFD) solver. Our simulation results demonstrated that flexible wings generated greater cycle-averaged aerodynamic forces compared to purely rigid flapping wings, underscoring the aerodynamic advantages of wing flexibility. Additionally, flexible wings produced 25% greater odor intensity, enhancing the insect's ability to detect and interpret olfactory cues. This study not only advances our understanding of the intricate interplay between wing motion, aerodynamics, and olfactory capabilities in flying insects but also raises intriguing questions about the intentional modulation of flow fields for sensory purposes in other behaviors.
Increased transparency in accounting conventions could benefit climate policy
Authors: Wedderburn-Bisshop Gerard 
Published: February 2025

Abstract
Greenhouse gas accounting conventions were first devised in the 1990’s to assess and compare emissions. Several assumptions were made when framing conventions that remain in practice, however recent advances offer potentially more consistent and inclusive accounting of greenhouse gases. We apply these advances, namely: gross accounting of CO2 sources; linking land use emissions with sectors; using Effective Radiative Forcing (ERF) rather than Global Warming Potentials (GWPs) to compare emissions; including both warming and cooling emissions, and including loss of additional sink capacity (LASC). We compare these results with conventional accounting and find that this approach boosts perceived carbon emissions from deforestation, and finds agriculture, the most extensive land user, to be the leading emissions sector and to have caused 60% (32%-87%) of ERF change since 1750. We also find that fossil fuels are responsible for 18% of ERF, a reduced contribution due to masking from cooling co-emissions. We test the validity of this accounting and find it useful for determining sector responsibility for present-day warming and for framing policy responses, while recognising the dangers of assigning value to cooling emissions, due to health impacts and future warming.
Accelerating spiking neural networks with parallelizable leaky integrate-and-fire neurons
Authors: Yarga Sidi Yaya Arnaud , Wood Sean U. N. 
Published: February 2025

Abstract
Spiking Neural Networks (SNNs) express higher biological plausibility and excel at learning spatiotemporal features while consuming less energy than conventional Artificial Neural Networks (ANNs), particularly on neuromorphic hardware. The Leaky Integrate-and-Fire (LIF) neuron stands out as one of the most widely used spiking neurons in deep learning. However, its sequential information processing leads to slow training on lengthy sequences, presenting a critical challenge for real-world applications that rely on extensive datasets. This paper introduces the Parallelizable Leaky Integrate-and-Fire (ParaLIF) neuron, which accelerates SNNs by parallelizing their simulation over time, for both feedforward and recurrent architectures. Compared to LIF in neuromorphic speech, image and gesture classification tasks, ParaLIF demonstrates speeds up to 200 times faster and, on average, achieves greater accuracy with similar sparsity. When integrated into state-of-the-art architectures, ParaLIF's accuracy matches or exceeds the highest performance reported in the literature on various neuromorphic datasets. These findings highlight ParaLIF as a promising approach for the development of rapid, accurate and energy-efficient SNNs, particularly well-suited for handling massive datasets containing long sequences.
After Lights Out
Authors: Rosenmeyer Patricia A 
Published: February 2025

Abstract
This chapter focuses on the early lives of two prominent American classicists, Martin Ostwald (1922–2010) and Thomas G. Rosenmeyer (1920–2007) who fled Germany at the beginning of the Second World War and met in an internment camp in Canada where their lifelong friendship started. The chapter examines their German-Jewish educational background and explores through personal letters, diaries, and memoirs their shared experience of internment during which they continued to find ways to study and teach classical topics. The discussion explores the constitutive role of learning world literature, and especially Greek and Latin literature, in challenging times.
The Classical Turn in Hebrew Literature in the Early Twentieth Century
Authors: Cohen Yotam 
Published: February 2025

Abstract
At the turn of the nineteenth and twentieth centuries, which witnessed the growth of Jewish nationalism and the birth of modern Hebrew language and literature, literary editors were central agents of the classical world in the creation of modern Hebrew culture. They operated on the premise that, to transform Hebrew culture into a modern European-like culture, it had to adopt classical literature and values. This chapter focuses on the introduction of the classical legacy into Hebrew culture as part of the collective effort to create a modern Jewish state. The chapter thus examines attitudes to classical culture as reflected in the periodicals of that time: Ha-Shiloach, Ha-Tekufa, and the many editions of the Stiebel publishing house.
Economic Sanctions as State Crime: Empire, Law and the United States’ Economic Warfare in Latin America
Authors: Atiles Jose 
Published: February 2025

Abstract
This paper argues that US unilateral economic and financial sanctions on Latin American countries constitute state crime. Although critical scholarship on sanctions has shown that these coercive measures contravene international law and harm the populations of targeted countries, criminological scholarship has neglected the analysis of sanctions. Focusing on sanctions as structural violence, this paper explores how the power dynamics in imposing unilateral sanctions on Latin America align with understandings of state crimes and imperialism. The paper engages with the theoretical frameworks of state crime and the criminology of empire, provides an overview of US unilateral sanctions on Latin American countries, and suggests a research agenda for studying economic sanctions as state crime.