bluuebunny/crossref_metadata_2025 huggingface dataset:
Effective Strategy of Enhancing Piezoelectricity in Stable CrSiN4Sn Semiconductor Monolayers by Atom-Layer-Pair-Effect
Authors: He Qi-Wen , Zhu Dan-Yang , Wang Jun-Hui , Zhang He-Na , Shang Xiao , Cui Shou-Xin , Wang Xiao-Chun
Published: February 2025

It is a challenge to reveal the design strategy of strong piezoelectricity nano-materials applied for self-powered and smart nano-devices. The atom-layer-pair effect is found in MoSi
x
N
y

R

z
monolayers with remarkable piezoelectricity by first-principles calculations. The absolute values of the vertical piezoelectric coefficients have a linear relation with the total electronegativity difference dipole moments. Based on this effect, the promising CrSiN4Sn monolayer is found with the highest piezoelectricity among the above monolayers. The work expands our understanding of the piezoelectric physical mechanism and provides the design strategy for piezoelectric nano-devices.
Evaluation of Sinusoidal Wave Energy Dissipation over a Gyroid Triply Periodic Minimal Surface-based Porous Breakwater
Authors: Duy Khanh Le Thanh , Nguyen Khuong D.
Published: February 2025

Breakwaters with porosity have been considered one of the most prospective keys to the wave’s energy reduction issues in the shoreline engineering area. In this project, the specimen test would be a permeable porous breakwater design relied on the structural Triply Periodic Minimal Surface (TPMS) unit cells-Gyroid. The paper’s primary purpose is to utilize the numerical method Finite Volume Method (FVM) to evaluate approximately the wave’s dissipation before and after crashing against the structures. To be detailed, the experiment has two stages: validation and verification. For the first stage, to validate the accuracy of the mathematical sinusoidal wave model, a computational fluid dynamics software (CFD) Ansys Fluent was utilized to approximate the wave’s characteristics and compared with the empirical experiment, which is generated by a plunger-type wavemaker controlled with three different rounds per minute(RPM), separately 22(r/min), 44(r/min) and 66(r/min) in a wave flume without the breakwater. The wave’s characteristics, such as period T, wave height H, and wavelength L, would be considered in this process. Next, those set-ups are reapplied for a numerical wave tank containing the Gyroid breakwater to evaluate the effective performance regarding the wave prevention proficiency, based on the transmission coefficient (Ct
). In conclusion, the proposed wave model is validated, and there is a strong agreement between the numerical and experimental results. Finally, the Gyroid breakwater has exhibited outstanding efficacy in wave transmission reduction.
Positive Emotional State Recognition Using Nonlinear Dynamics Analysis and Machine Learning Algorithms with Electroencephalogram Signals
Authors: Gia Quynh Nguyen , Khai Le Quoc
Published: February 2025

Electroencephalogram (EEG) signals processing has gathered increased interest from the scientific community for a long time, especially in the field of emotion recognition. The objective of this research is to propose a method that analyzes EEG signals from a publicly available dataset called SJTU Emotion EEG Dataset (SEED) to classify different emotional states, especially positive emotions. The dataset consists of EEG signals recorded from fifteen subjects while watching different film clips, each of which corresponds to a type of emotions. Initial analysis involves the extraction of features from the pre-processed data including time-domain analysis, frequency-domain analysis using Fast Fourier Transform (FFT) and nonlinear dynamics method. Machine learning algorithms are then applied as classifiers in order to determine the emotional states of each subject – categorized as positive, negative, or neutral – with the input is the extracted features. In this work, Support Vector Machine (SVM), Linear Discriminant Analysis (LDA) and Subspace Discriminant (SD) are used for training and testing the labeled data. The classification step achieved the highest accuracy level of 82.2% while the highest micro-F1 score value is 0.92 for positive emotions. The established methodology not only proposes an automated model for determining positive emotional states but also plays an important role at the beginning of the investigation further into emotion recognition by providing better visualization of how different emotional states are determined.
Applying convolutional neural networks in identifying and classifying Acute Lymphocytic Leukemia and its subtypes using Matlab
Authors: Huy Phan Nguyen Bao , Hau Tran Thien , Anh Tu Tran
Published: February 2025

Leukemia is a blood cancer originating in the bone marrow that leads to the production of abnormal blood cells, impacting cell functionality and efficiency. According to Globocan, statistics for 2022 show that Viet Nam has 180,480 new cancer cases and 120,184 deaths, of which leukemia has 5,789 new cases, ranking 8th among cancer types (accounting for 3.2%) and 4,330 deaths, ranking 6th in mortality rate among cancer types (accounting for 3.6%). Depending on the progression rate, leukemia can be identified as either acute or chronic. Acute leukemia affects blood cells in the early stages of development, causing the disease to become more severe, while chronic leukemia affects more developed blood cells, and the disease tends to develop slowly. Another way to classify leukemia is by the specific blood cell type it targets, either myeloid or lymphoid cells. Understanding the affected cell type is essential for diagnosis and treatment planning, as it influences disease behavior and response to treatment. This paper focuses on identifying and classifying ALL (Acute Lymphoblastic Leukemia) blasts in the most prevalent childhood cancer type using transfer learning of the Alexnet network model in Matlab software. Diagnosing ALL disease using peripheral blood smear (PBS) images helps screen and treat the disease early, contributing to improving treatment effectiveness for patients. Laboratory users often face challenges when examining PBS images, as the non-specific signs and symptoms of ALL can result in frequent misdiagnoses and diagnostic errors. The research presents a model for analyzing peripheral blood smear images, aimed at identifying ALL cell types and distinguishing among its malignant subtypes. The ALexnet model will be trained in 3 different ways including: Train with no parameters (Training a Neural Network from Scratch), train the pretrained network but change the fullyConnected layer at the end and train the pretrained network but change the 14th layer onwards. The results show that the model using the second training method achieves the best performance when reaching 98.664% accuracy on the validation set, while methods 1 and 3 are 92.292% and 89.825% respectively. Finally, the second model is saved to design the user application using AppDesigner.
Application of infrared technique in identifying white spot lesions
Authors: Pham Thi Hai Mien
Published: February 2025

White spot lesions are early – stage dental lesions which are difficultly identified and analysed by common diagnostic methods such as clinical examination or radiography. In contrast, in recent years, a number of research has showed that the infrared technique could be applied for identifying early – stage dental damages like white spot lesions due to the difference in optical properties between damaged and healthy tooth tissues. Sound enamel is nearly transparent under infrared light while damaged tissues appear darker. The aim of the present study was to apply the infrared technique to identification of white spot lesions at early stages. In this research, the optical system with 850-nm LEDs was designed and manufactured based on scattering and transmission techniques, and used for observing in vitro the tooth sample with white spot lesions. A number of 100 tooth samples were diagnosed with the infrared technique and traditional methods (clinical observation and radiography) at the same time. Then, Cohen’s Kappa coefficient was figured to evaluate the agreement in diagnosis between the mentioned methods. The low Kappa coefficient (only 0.01) indicates the low consensus between clinical – radiography assessment and the infrared technique. This result is reasonable due to the fact that the infrared technique is highly capable of detecting demineralized damages like white spot lesions whereas both clinical examination and radiography have low sensitivity in identifying this type of lesions.
Classification of Lumbar Spine Degeneration Using Vision Transformer with the RSNA Dataset
Authors: Huynh Hoang Nhut , Ngoc An Dang Nguyen , Nguyen Trung An Dang , Phan Minh Hoang , Nguyen Van Chinh , Tran Trung Nghia
Published: February 2025

This study presents a deep-learning approach for classifying lumbar spine degeneration using the RSNA dataset by employing a Vision Transformer model. The classification task was divided into three categories normal/mild, moderate, and severe. The dataset comprises approximately 2000 MRI studies annotated by spine radiology specialists to indicate the presence, vertebral level, and location of any lumbar spinal stenosis. The methodology involves preprocessing the MRI and training a Vision Transformer to classify degeneration severity. The Vision Transformer model was chosen for its ability to capture global image dependencies and superior performance in medical image analysis tasks. The quantitative results demonstrate the effectiveness of our approach, with an accuracy of 93.6%, a precision of 92.3%, and a recall of 89.8%. The proposed method achieves high classification performance and aids in the early detection and treatment planning for lumbar spine degeneration. The significance of this research lies in its potential to automate and enhance the diagnostic process, providing reliable and rapid assessments that can support clinical decision-making and improve patient outcomes.
Assessment of the lateral displacement of a single pile in the sloping ground based on finite element analysis method
Authors: Chau Phuong Khanh , Tuan Le Anh , Duong Ngoc Tran , Danh Thanh lam , Nguyen Tan Hung
Published: February 2025

The current study observed the effect of embankment height, pile diameter, and pile length on the lateral displacement of the reinforced concrete pile installed in the sloping ground using the finite element analysis program. While the embankment height in the study was 1.5, 3.0, and 4.5 m, the pile diameter was 0.25, 0.5, and 1.0 meters. The pile length was chosen as 10, 15, and 20 m for the analysis. This study figured that the embankment height affected remarkably the lateral displacement of the pile (LDP). As the height of the embankment increased, the LDP increased. Results of the LDP in the case of difference in pile diameter were similar. It could be seen that the pile diameter did not affect the LDP in the sloping ground. Finally, the study for the effect of pile embedment length showed that for the pile head, a pile with a longer embedment length resulted in a smaller lateral displacement. However, for the pile toe, piles with different embedment lengths produced similar lateral displacements. It is noted that the current study only evaluated the effect of embankment height, pile diameter, and pile length on the LDP based on the finite element analysis. Further studies on the effects of these factors based on experimental evaluation should be carried out.
The Modeling of Non-invasive Measurement of Fruit Sweetness using Near-Infrared (NIR) Spectroscopy Method
Authors: Tran Hong Duyen Trinh , Anh Tu Tran
Published: February 2025

The sugary content in fruit requires knowledge for both the maker and the consumer. Methods of evaluating the level of sweetness in fruits as previously described, for example through chemical means, is a long and tedious process. This paper demonstrates the benefits of using NIR in determining fruit sweetness as a rapid, non-destructive, and accurate technique compared to the conventional methods. Near infrared spectroscopy (NIR spectroscopy) is a rapid non-destructive technique for measuring the physical and chemical properties of fruit by analyzing the light absorption in the proximal part of infrared spectrum (780-2500 nm). This paper aims to determine the potential of applying food quality NIR spectroscopy spot check, at a wavelength of 940 nm, in the reflectance mode for the evaluation of the sweetness of apples. When light from a 940 nm LED is directed to illuminate the surface of the fruit, some of it is absorbed while the rest is reflected. The reflected light is detected using a photodiode then converted to an electrical quantity using a conversion circuit after which it is passed to a microcontroller. The study was conducted on 30 different apple samples to develop a model, with sweetness quantified using a Brix refractometer. The obtained results were used to construct a linear regression model, showing the correlation between the measured voltage values and the Brix values. The model yielded a correlation coefficient (R²) of 0.6261, demonstrating the feasibility of using the 940 nm near-infrared wavelength to non-invasively measure fruit sweetness. These preliminary results help us understand the experimental design and develop techniques to measure fruit sweetness using light at other wavelengths in the future.
An Optimal Method for Calculating Suspension Spring Stiffness Based on Roll Angle and Roll Acceleration Values
Authors: Nguyen Ngoc Tram , Nguyen Duc Ngoc , Pham Huu Dong , Nguyen Manh Long , Nguyen Tuan Anh
Published: February 2025

The stiffness of the suspension spring plays a vital role in maintaining the vehicle’s ride comfort during vibration. An optimal calculation method is proposed in this paper to find the ideal stiffness value of the suspension spring. Firstly, a half-dynamic model is established to describe the vehicle’s vibration. Then, an optimal calculation method is formulated, which consists of two steps: running the loop to find the Root Mean Square (RMS) values of the vibration and determining the ideal stiffness value based on finding the minimum values of roll angle and roll acceleration. According to the study’s findings, the ideal stiffness of the suspension spring is 36900 N/m, obtained in the first case. Even when the excitation amplitude increases (in the second case), the ideal stiffness value is still 36900 N/m, achieved using the proposed method. This helps to demonstrate the correctness of the optimal method established in this paper. Finally, the vehicle vibration is investigated using the optimal stiffness value above.
Studying the Large Span Multi-Cell Steel Box Girder – An Engineering Mechanics Look
Authors: Duong Tham Hong
Published: February 2025

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

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

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

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

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

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

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

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

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

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

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

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.
Intracellular diffusion in the cytoplasm increases with cell size in fission yeast
Authors: Tan Catherine , Lanz Michael C. , Swaffer Matthew , Skotheim Jan , Chang Fred
Published: February 2025

Diffusion in the cytoplasm can greatly impact cellular processes, yet regulation of macromolecular diffusion remains poorly understood. There is increasing evidence that cell size affects the density and macromolecular composition of the cytoplasm. Here, we studied whether cell size affects diffusion at the scale of macromolecules tens of microns in diameter. We analyzed the diffusive motions of intracellular genetically-encoded multimeric 40 nm nanoparticles (cytGEMs) in the cytoplasm of the fission yeast Schizosaccharomyces pombe. Using cell size mutants, we showed that cytGEMs diffusion coefficients decreased in smaller cells and increased in larger cells. This increase in diffusion in large cells may be due to a decrease in the DNA-to-Cytoplasm ratio, as diffusion was not affected in large multinucleate cytokinesis mutant cells. In investigating the underlying causes of altered cytGEMs diffusion, we found that the proteomes of large and small cells exhibited size-specific changes, including the sub-scaling of ribosomal proteins in large cells. Comparison with a similar dataset from human cells revealed that features of size-dependent proteome remodeling were conserved. These studies demonstrate that cell size is an important parameter in determining the biophysical properties and the composition of the cytoplasm.
After Lights Out
Authors: Rosenmeyer Patricia A
Published: February 2025

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

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

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.
Carbohydrate antigen 19-9 (CA19-9) response after induction FOLFIRINOX for locally advanced pancreatic cancer identifies patients who may benefit from surgical exploration: multicentre, observational cohort study
Authors: Dekker Esther N , van Klaveren David , Verkolf Eva M M , de Wilde Roeland F , Besselink Marc G , O’Reilly Eileen M , Paniccia Alessandro , Katz Matthew H G , Tzeng Ching-Wei D , Wei Alice C , Zureikat Amer H , Groot Koerkamp Bas ,   the Trans-Atlantic Pancreatic Surgery (TAPS) Consortium, el Asmar R , DeSilva A , Haviland D , Ilagan C , Janssen Q P , McIntyre S , Prakash L R , Theijse R T
Published: February 2025

Background

Which patients with locally advanced pancreatic cancer may benefit from surgical exploration after induction treatment remains debated. The aim of this retrospective cohort study was to identify independent factors for overall survival after surgical exploration for locally advanced pancreatic cancer, which are available at restaging after induction therapy.

Methods

Consecutive patients with locally advanced pancreatic cancer from the Trans-Atlantic Pancreatic Surgery cohort who underwent surgical exploration after FOLFIRINOX as induction chemotherapy were included. Multivariable Cox proportional hazards analyses with contour plots were used for the predicted 3-year overall survival in patients who underwent surgical exploration.

Results

Overall, 958 patients with locally advanced pancreatic cancer were treated with FOLFIRINOX as induction therapy. At restaging, 221 patients (23.1%) had metastatic disease (M1) and 724 patients (75.6%) did not have metastatic disease (M0)—234 patients (24.4%) with M0 disease underwent surgical exploration and 490 patients (51.1%) with M0 disease did not undergo surgical exploration; restaging information was not available for 13 patients (1%). The surgical exploration cohort included 213 patients with locally advanced pancreatic cancer, after excluding 21 carbohydrate antigen 19-9 non-producers. The independent prognostic factors for overall survival after surgical exploration were post-induction carbohydrate antigen 19-9 level (HR 1.14 (95% c.i. 1.01 to 1.29)), carbohydrate antigen 19-9 decrease (HR 0.89 (95% c.i. 0.79 to 0.99)), and a WHO performance status of greater than or equal to one (HR 1.71 (95% c.i. 1.21 to 2.42)). Baseline carbohydrate antigen 19-9 was not prognostic for overall survival after surgical exploration (HR 0.98 (95% c.i. 0.90 to 1.07)). The best predicted 3-year overall survival was achieved with a greater than 80% decrease in carbohydrate antigen 19-9 and a post-induction carbohydrate antigen 19-9 less than 50 U/ml.

Conclusion

Carbohydrate antigen 19-9 after induction therapy, carbohydrate antigen 19-9 decrease, and performance status are independent prognostic factors for overall survival after surgical exploration for locally advanced pancreatic cancer. Three-year overall survival is best in patients with a performance status of zero, a greater than 80% decrease in carbohydrate antigen 19-9, and a post-induction carbohydrate antigen 19-9 level less than 50 U/ml.
The blood–brain barrier: a help and a hindrance
Authors: Rust Ruslan , Yin Hao , Achón Buil Beatriz , Sagare Abhay , Kisler Kassandra
Published: February 2025

The blood-brain barrier (BBB) is a specialized vascular structure that protects the brain microenvironment from toxins and pathogens in the blood. At the same time, the BBB presents a significant challenge for drug development, as it restricts the entry of most therapeutics into the brain. In this review, we first examine recent findings on the molecular and cellular architecture of the BBB, emphasizing the diverse mechanisms that facilitate the transport and exchange of molecules between the blood and the brain. We discuss current knowledge on the heterogeneity of the BBB along the arteriovenous axis and across different brain regions. Then, we explore the molecular and functional changes in the BBB that occur during normal aging, neurodegeneration, and acute brain injuries and how prolonged BBB impairment affects transport mechanisms and disease progression. Additionally, we discuss novel developments in drug delivery strategies to transport small molecules, biologicals or cellular therapeutics across the BBB. Finally, we examine therapeutic opportunities to restore the BBB and discuss future directions in the field.
The neural characteristics influencing literacy outcome in children with cochlear implants
Authors: Koirala Nabin , Manning Jacy , Neumann Sara , Anderson Chelsea , Deroche Mickael L D , Wolfe Jace , Pugh Kenneth , Landi Nicole , Muthuraman Muthuraman , Gracco Vincent
Published: February 2025

Early hearing intervention in children with congenital hearing loss is critical for improving auditory development, speech recognition, and both expressive and receptive language which translates into better educational outcomes and quality of life. In children receiving hearing aids or cochlear implants (CI), both adaptive and potentially maladaptive neural reorganization can mitigate higher level functions that impact reading. The focus of the present study was to dissect the neural underpinnings of the reading networks in children with cochlear implants and assess how these networks mediate the reading ability in children with cochlear implants.

Cortical activity was obtained using naturalistic stimuli from 75 children (50 cochlear implant recipients, aged 7 to 17, and 25 age-matched children with typical hearing (TH)) using functional Near Infrared Spectroscopy (fNIRS). Assessment of basic reading skill was completed using the Reading Inventory and Scholastic Evaluation (RISE). We computed directed functional connectivity of the hemodynamic activity in reading-associated anterior and posterior brain regions using the time-frequency causality estimation method known as temporal partial directed coherence. The influence of the cochlear implant-related clinical measures on reading outcome and the extent to which neural connectivity mediated these effects were examined using structural equation modelling.

Our findings reveal that the timing of intervention (e.g., age of first cochlear implants, age of first hearing aid) in children with cochlear implants significantly influenced their reading ability. Furthermore, reading related processes (word recognition and decoding, vocabulary, morphology and sentence processing) were substantially mediated by the directed functional connectivity within reading-related neural circuits. Notably, the impact of these effects differed across various reading skills. Hearing age, defined as the age at which a participant received adequate access to sound, and age of initial implantation emerged as robust predictors of reading proficiency.

The current study is one of the first to identify the influence of neural characteristics on reading outcomes for children with cochlear implants. The findings emphasize the importance of duration of deafness and early intervention for enhancing outcomes and strengthening neural network connections. However, the neural evidence further suggested that such positive influences cannot fully offset the detrimental impact of early auditory deprivation. Consequently, additional, perhaps more specialized, interventions might be necessary to maximize the benefits of early prosthetic hearing intervention.
A practical and versatile synthetic strategy for homogeneous polymers of 1,3-propanediamine
Authors: Ohnishi Taiga , Irie Raku , Inai Makoto , Kan Toshiyuki , Oikawa Masato
Published: February 2025

A convergent, iterative, and split-couple strategy for synthesis of homogeneous polymer of 1,3-propanediamine (long-chain polyamine, LCPA) has been developed, by employing 1,3-dibromopropane as a glue in subunit couplings. By this synthetic strategy, 7-, 11-, and 15-mer LCPAs were successfully synthesized. This synthetic strategy solved problems that had arisen with previous methods, such as variable reactivity and poor reproducibility.
The right ventricle: the co-star in the complex history of heart failure
Authors: Manzi Giovanna , Recchioni Tommaso , Mihai Alexandra , Severino Paolo , Birtolo Lucia Ilaria , Filomena Domenico , D’Amato Andrea , Mancone Massimo , Papa Silvia , Badagliacca Roberto , Vizza Carmine Dario
Published: February 2025

The natural history of patients with heart failure (HF), mainly affecting the left ventricle in the initial stages, is marked by the progressive involvement of the right ventricle (RV), which in the advanced stages of the disease becomes dilated and dysfunctional. The geometrical, functional, and pathological interdependence binding the two ventricles underlies this progressive path. Researchers’ and clinicians’ efforts must be aimed at interrupting the inevitable trajectory of HF, by preventing the development of pulmonary hypertension (PH) and RV dysfunction or the transition from isolated post-capillary PH to combined pre- and post-capillary PH. The search for drugs targeting the pulmonary circulation is another goal of PH researchers. Studies conducted so far on drugs currently approved for patients with pulmonary arterial hypertension have yielded contradictory results; an in-depth analysis of these trials could help researchers profile the patients with HF who might benefit from these treatments.