bluuebunny/crossref_metadata_2025 huggingface dataset:
Point-of-Care Ultrasound in Nephrology: Beyond Kidney Ultrasound
Authors: Gómez-Johnson Victor Hugo , López-Gil Salvador , Argaiz Eduardo R. , Koratala Abhilash
Published: January 2025

Point-of-care ultrasound (POCUS) has increasingly become an integral part of clinical practice, particularly in nephrology, where its use extends beyond renal assessment to include multi-organ evaluations. Despite challenges such as limited ultrasound training and equipment access, especially in low- and middle-income countries, the adoption of POCUS is steadily rising. This narrative review explores the growing role of multi-organ POCUS in nephrology, with applications ranging from the assessment of congestion phenotypes, cardiorenal syndrome, and hemodynamic acute kidney injury (AKI) to the evaluation of arteriovenous fistulas and electrolyte disorders. In nephrology, POCUS enhances clinical decision making by enabling rapid, bedside evaluations of fluid status, cardiac function, and arteriovenous access. Studies have demonstrated its utility in diagnosing and managing complications such as heart failure, cirrhosis, and volume overload in end-stage renal disease. Additionally, POCUS has proven valuable in assessing hemodynamic alterations that contribute to AKI, particularly in patients with heart failure, cirrhosis, and systemic congestion. This review highlights how integrating ultrasound techniques, including lung ultrasound, venous Doppler, and focused cardiac ultrasound, can guide fluid management and improve patient outcomes. With advancements in ultrasound technology, particularly affordable handheld devices, and the expansion of targeted training programs, the potential for POCUS to become a global standard tool in nephrology continues to grow, enabling improved care in diverse clinical settings.
Engineered Prompts in ChatGPT for Educational Assessment in Software Engineering and Computer Science
Authors: Diyab Ayman , Frost Russell Morris , Fedoruk Benjamin David , Diyab Ahmad
Published: January 2025

AI Assess, a ChatGPT-based assessment system utilizing the ChatGPT platform by OpenAI, composed of four components, is proposed herein. The components are tested on the GPT model to determine to what extent they can grade various exam questions based on learning outcomes, generate relevant practice problems to improve content retention, identify student knowledge gaps, and provide instantaneous feedback to students. The assessment system has been explored using software engineering and computer science courses and is successful through testing and evaluation. AI Assess has demonstrated the ability to generate practice problems based on syllabus information and learning outcomes. The components have been shown to identify weak areas for students. Finally, it has been shown to provide different levels of feedback. The combined set of components, if incorporated into a complete software system and implemented in classrooms with proposed transparency mechanisms, has vast potential to reduce instructor workload, improve student understanding, and enhance the learning experience. The potential for GPT-powered chatbots in educational assessments is vast and must be embraced by the education sector.
A Deepfake Image Detection Method Based on a Multi-Graph Attention Network
Authors: Chen Guorong , Du Chongling , Yu Yuan , Hu Hong , Duan Hongjun , Zhu Huazheng
Published: January 2025

Deep forgery detection plays a crucial role in addressing the challenges posed by the rapid spread of deeply generated content that significantly erodes public trust in online information and media. Deeply forged images typically present subtle but significant artifacts in multiple regions, such as in the background, lighting, and localized details. These artifacts manifest as unnatural visual distortions, inconsistent lighting, or irregularities in subtle features that break the natural coherence of the real image. To address these features of forged images, we propose a novel and efficient deep image forgery detection method that utilizes Multi-Graph Attention (MGA) techniques to extract global and local features and minimize accuracy loss. Specifically, our method introduces an interactive dual-channel encoder (DIRM), which aims to extract global and channel-specific features and facilitate complex interactions between these feature sets. In the decoding phase, one of the channels is processed as a block and combined with a Dynamic Graph Attention Network (PDGAN), which is capable of recognizing and amplifying forged traces in local information. To further enhance the model’s ability to capture global context, we propose a global Height–Width Graph Attention Module (HWGAN), which effectively extracts and associates global spatial features. Experimental results show that the classification accuracy of our method for forged images in the GenImage and CIFAKE datasets is comparable to that of the optimal benchmark method. Notably, our model achieves 97.89% accuracy on the CIFAKE dataset and has the lowest number of model parameters and lowest computational overhead. These results highlight the potential of our method for deep forgery image detection.
A Personalized Federated Learning Algorithm Based on Dynamic Weight Allocation
Authors: Liu Yazhi , Li Siwei , Li Wei , Qian Hui , Xia Haonan
Published: January 2025

Federated learning is a privacy-preserving distributed machine learning paradigm. However, due to client data heterogeneity, the global model trained by a traditional federated averaging algorithm often exhibits poor generalization ability. To mitigate the impact of data heterogeneity, some existing research has proposed clustered federated learning, where clients with similar data distributions are grouped together to reduce interference from dissimilar clients. However, since the data distribution of clients is unknown, determining the optimal number of clusters is difficult, leading to reduced model convergence efficiency. To address this issue, this paper proposes a personalized federated learning algorithm based on dynamic weight allocation. First, each client is allowed to obtain a global model tailored to fit its local data distribution. During the client model aggregation process, the server first computes the similarity of model updates between clients and dynamically allocates aggregation weights to client models based on these similarities. Secondly, clients use the received exclusive global model to train their local models via the personalized federated learning algorithm. Extensive experimental results demonstrate that, compared to other personalized federated learning algorithms, the proposed method effectively improves model accuracy and convergence speed.
The Progress and Prospects of Data Capital for Zero-Shot Deep Brain–Computer Interfaces
Authors: Ma Wenbao , Ma Teng , Organisciak Daniel , Waide Jude E. T. , Meng Xiangxin , Long Yang
Published: January 2025

The vigorous development of deep learning (DL) has been propelled by big data and high-performance computing. For brain–computer interfaces (BCIs) to benefit from DL in a reliable and scalable manner, the scale and quality of data are crucial. Special emphasis is placed on the zero-shot learning (ZSL) paradigm, which is essential for enhancing the flexibility and scalability of BCI systems. ZSL enables models to generalise from limited examples to new, unseen tasks, addressing data scarcity challenges and accelerating the development of robust, adaptable BCIs. Despite a growing number of BCI surveys in recent years, there is a notable gap in clearly presenting public data resources. This paper explores the fundamental data capital necessary for large-scale deep learning BCI (DBCI) models. Our key contributions include (1) a systematic review and comprehensive understanding of the current industrial landscape of DBCI datasets; (2) an in-depth analysis of research gaps and trends in DBCI devices, data and applications, offering insights into the progress and prospects for high-quality data foundation and developing large-scale DBCI models; (3) a focus on the paradigm shift brought by ZSL, which is pivotal for the technical potential and readiness of BCIs in the era of multimodal large AI models.
A 64 × 1 Multi-Mode Linear Single-Photon Avalanche Detector with Storage and Shift Reuse in Histogram
Authors: Lv Hankun , Wang Jingyi , Chen Bu , Huang Zhangcheng
Published: January 2025

Single-photon avalanche detectors (SPADs) have significant applications in fields such as autonomous driving. However, processing massive amounts of background data requires substantial storage and computational resources. This paper designs a linear SPAD sensor capable of three detection modes: 2D intensity detection, 3D synchronous detection, and 3D asynchronous detection. A configurable coincidence circuit is used to effectively suppress background light. To overcome the significant resource demands for storage and computation, this paper designs a histogram circuit that simultaneously possesses data storage and shifting capabilities. This circuit can not only perform statistical counting on time data but also shift data to quickly complete computational analysis. The chip is fabricated using a 0.13 μm mixed-signal CMOS process, with a pixel scale of 64 elements, a time resolution of 132 ps, and a power consumption of 12.9 mW. Test results indicate that the chip has good detection capabilities and good background light suppression. When the background light intensity is 6000 lux, the maximum background data are suppressed by 95.4%, and the average suppression rate increases to 86% as the coincidence threshold is raised from 0 to 1.
FeatherFace: Robust and Lightweight Face Detection via Optimal Feature Integration
Authors: Kim Dohun , Jung Jinmyung , Kim Jinhyun
Published: January 2025

Face detection in resource-constrained environments presents challenges, due to the computational demands of state-of-the-art models and the complexity of real-world conditions, such as variations in scale, pose, and occlusion. This study introduces FeatherFace, a lightweight face-detection architecture with only 0.49 M parameters, designed for high accuracy and efficiency in such environments. Leveraging MobileNet-0.25 as a backbone, FeatherFace incorporates advanced feature-integration strategies, including a bidirectional feature pyramid network (BiFPN), a convolutional block attention module (CBAM), deformable convolutions, and channel shuffling. Evaluated on the WIDERFace dataset, FeatherFace achieves an overall average precision (AP) of 87.2%, with notable performance gains of 4.0% AP on the Hard subset compared with the baseline. Ablation studies highlight the critical role of multiscale feature integration and the strategic placement of attention mechanisms in addressing detection challenges such as small or occluded faces. With its compact design and reduced inference time, FeatherFace bridges the gap between the reliability of computationally intensive models and the need for deploying robust models in highly resource-constrained environments, such as edge devices and embedded systems. This work provides valuable insights for developing robust and lightweight models suited to challenging real-world applications.
Structural and Modal Analysis of a Small Wind Turbine Blade Considering Composite Material and the IEC 61400-2 Standard
Authors: Vázquez Miriam , López Victor , Campos Rafael , Cadenas Erasmo , Marin Paulina
Published: January 2025

IEC 61400-2 establishes the Simplified Load Method for designing low-power wind turbine blades without considering dynamic loads in the simplified load methodology. This paper analyzes the load hypotheses established by the standard, also considering the natural frequencies in a 900 W blade. The research methodology begins with the design parameters, the application of the BEM Method, and the use of the QBlade software. Then, the load hypotheses of the standard are defined. Finally, the structural design and the modal and structural analysis of the blade were conducted using FEM-based software. The results show that the minimum participation factors are found on the z-axis and the maximum on the x- and y-axis, and their magnitudes decrease when the natural frequency increases. In general, the principal maximum stresses are located in the middle section of the blade, in the external fiberglass layer, both on the intrados and extrados sides. In conclusion, structural scenarios were established to relate the participation factors of the modal analyses with the load hypotheses. The critical scenarios are at natural frequencies below 280 Hz.
Use of Kinetic Parameters from Thermal Analysis for Balancing Free Energy of Activation Based on Calcite Decomposition
Authors: Mianowski Andrzej , Bigda Rafał
Published: January 2025

Based on the literature data, including our published paper on the thermal decomposition of solids, research regarding the possibility of balancing free energy of activation against Gibbs free energy was extended. The importance of nucleation accompanying the thermal decomposition reaction/process was established. For calcite, a symmetrical model was considered for the formation of the active state, followed by the formation into the solid, crystalline decomposition product CaO. When the decomposition is chemical in nature, we do not identify nucleation processes. This is determined by the forwards–backwards balance compatibility, and when an additional term appears, a reversible structural transformation is to be expected. An excess free energy model was proposed to determine the rate constant of activation. It is shown that the results of tests under dynamic conditions allow, with a good approximation, the determination of this quantity as tending towards a maximum rate constant equal to the Arrhenius pre-exponential factor. The solid product of the thermal decomposition of calcite is of great developmental importance, currently utilized for Calcium Looping (CaL) or for Carbon Capture and Storage (CCS) technologies using a reversible reaction of carbonation.
Horizontal Cyclic Bearing Characteristics of Bucket Foundation in Sand for Offshore Wind Turbines
Authors: Zhai Hanbo , Zhang Puyang , Ren Junqi
Published: January 2025

During the service period, the offshore wind turbine foundation mainly bears the wind load from the upper structure and the periodic loads such as wave load and sea currents from the lower structure. Long-term cyclic loads have an important impact on the cumulative deformation, foundation stiffness changes, and horizontal ultimate bearing capacity of the offshore wind turbine bucket foundation. This paper conducts cyclic loading tests on mono-bucket foundations under unidirectional and multidirectional cyclic loading conditions based on the multidirectional intelligent cyclic loading system of offshore wind turbine foundations and analyzes the cumulative effects of the loading direction, vertical load, and drainage status on the mono-bucket foundation during the cyclic loading process, effects of rotation angle, cyclic stiffness, and monotonic bearing capacity of foundation after cycles. The research results show that multidirectional cyclic loading significantly reduces the cyclic cumulative rotation angle of the mono-bucket foundation, and the maximum reduction rate can reach more than 50%. After unidirectional and multidirectional cyclic loading, the bearing capacity of the bucket foundation can be increased by up to 30% and 20%, respectively. At the same time, this paper proposes calculation formulas for vertical load, number of cyclic loading, and normalized cumulative rotation and establishes a calculation method for vertical load and bearing capacity of the foundation after cycles.
Multi-Objective Dynamic System Model for the Optimal Sizing and Real-World Simulation of Grid-Connected Hybrid Photovoltaic-Hydrogen (PV-H2) Energy Systems
Authors: Atteya Ayatte I. , Ali Dallia , Sellami Nazmi
Published: January 2025

Hybrid renewable-hydrogen energy systems offer a promising solution for meeting the globe’s energy transition and carbon neutrality goals. This paper presents a new multi-objective dynamic system model for the optimal sizing and simulation of hybrid PV-H2 energy systems within grid-connected buildings. The model integrates a Particle Swarm Optimisation (PSO) algorithm that enables minimising both the levelised cost of energy (LCOE) and the building carbon footprint with a dynamic model that considers the real-world behaviour of the system components. Previous studies have often overlooked the electrochemical dynamics of electrolysers and fuel cells under transient conditions from intermittent renewables and varying loads, leading to the oversizing of components. The proposed model improves sizing accuracy, avoiding unnecessary costs and space. The multi-objective model is compared to a single-objective PSO-based model that minimises the LCOE solely to assess its effectiveness. Both models were applied to a case study within Robert Gordon University in Aberdeen, UK. Results showed that minimising only the LCOE leads to a system with a 1000 kW PV, 932 kW electrolyser, 22.7 kg H2 storage tank, and 242 kW fuel cell, with an LCOE of 0.366 £/kWh and 40% grid dependency. The multi-objective model, which minimises both the LCOE and the building carbon footprint, results in a system with a 3187.8 kW PV, 1000 kW electrolyser, 106.1 kg H2 storage tank, and 250 kW fuel cell, reducing grid dependency to 33.33% with an LCOE of 0.5188 £/kWh.
Navigating Socio-Technical Challenges in Energy Efficiency: Case Studies on Hybrid Pumped-Hydropower Storage in Poland and Greece
Authors: Kruczek Mariusz , Markowska Malgorzata , Servou Aikaterini , Roumpos Christos , Mertiri Eleni , Ernst Priscilla , Darmosz Jaroslaw , Kempka Thomas
Published: January 2025

This study examines the socio-technical challenges and public acceptance of hybrid pumped-hydropower storage (HPHS) technology within the broader context of energy transition in two European coal-mining regions: Western Macedonia, Greece, and the Łódzkie Region, Poland. These regions, deeply rooted in lignite mining, face profound socio-economic transformations driven by the EU Green Deal and its commitment to achieving net-zero emissions by 2050. The transition from coal dependency to renewable energy represents not only a critical environmental goal but also a significant socio-economic challenge for local communities, necessitating innovative and inclusive strategies to mitigate impacts and ensure equitable outcomes. The research integrates desk studies with stakeholder surveys (n = 129) to assess public awareness, perceived impacts, and acceptance of HPHS technology as a repurposing solution for decommissioned open-pit lignite mines. Results reveal that while awareness of the energy transition process is high (90% in Western Macedonia and 80% in Łódzkie Region), familiarity with HPHS technology varies significantly (76% and 48%, respectively). Support for implementing HPHS in former mining sites is stronger in Western Macedonia (73%) compared to Łódzkie Region (63%), with knowledge of HPHS correlating positively with acceptance (r = 0.83, p < 0.01). Both regions recognize the environmental benefits of HPHS, including improved air quality and biodiversity; yet, socio-economic challenges such as job losses, reduced income levels, and limited opportunities for reskilling persist, particularly in Łódzkie Region, where 77% of respondents view the energy transition as negatively impacting the labor market. By focusing on regions historically dependent on mining, this study highlights the critical role of addressing the unique needs of communities undergoing systemic transformation. The repurposing of former lignite mines into HPHS facilities offers a promising pathway for balancing environmental objectives with local socio-economic revitalization. However, success requires region-specific strategies, including transparent communication, stakeholder involvement, and targeted investment in workforce adaptation and infrastructure. These findings contribute to the growing discourse on how socially inclusive and technically feasible solutions can drive equitable energy transitions in post-mining regions.
Characteristics and Optimization of Transient Process of Pump-Turbine Units in Power Generation Mode
Authors: Zhang Minglu , Liu Jie , Yu Junqin , Nie Changhua
Published: January 2025

Pumped storage power is considered an ideal regulated power source for new energy. However, the traditional one-dimensional characteristic line method cannot predict the pulsating pressure caused by the reverse “S” characteristic of a pump–turbine. In this paper, a variable-step Euler algorithm is presented to calculate the hydraulic transient process of pumped storage units, the interval times of start-up and load regulation between two pump–turbine units are investigated by using the method of peak staggering and valley filling, and the closure law of guide vanes in the transient process of load rejection is optimized. The results show that the presented method is valid, and that pulsating pressure is accurately captured during the transient process of load rejection. The water level fluctuation amplitude in the surge chamber is greatly reduced by the sequential start-up mode. The rotational speed fluctuation amplitude of the sequential load reduction is also reduced. After the load of two pump–turbine units is rejected at the same time, the duration of pulsating pressure in the spiral case is shortened by 45% by using the quick-then-slow closure law compared with the straight-line closure law. Moreover, the pulsating pressure amplitude and the second peak value of rotational speed are also reduced accordingly, and the transient characteristics of the pump–turbine units are greatly improved.
Growth Response of Pinus tabuliformis and Abies fargesii to Climate Factors in Southern Slope of Central Qinling Mountains of China
Authors: Chen Qingmin , Liu Na , Bao Guang , Cheng Xing , Wang Yanchao , He Kaikai , Zhang Wenshuo , Wang Gaohong
Published: January 2025

The response of trees to climate is crucial for the health assessment and protection of forests in alpine regions. Based on samples of Pinus tabuliformis and Abies fargesii, two typical evergreen coniferous species with distinct elevation differences in the vertical vegetation zones of the Qinling Mountains, we have developed two tree-ring width chronologies for the southern slope of the central Qinling Mountains in central China. The correlation analysis results showed that the radial growth of P. tabuliformis and A. fargesii responded to different climatic factors. Water stress caused by temperature in May of the current year was the main limiting factor for radial growth of P. tabuliformis, while precipitation in September of the previous year and the current year had a negative impact on A. fargesii, with lag effects of temperature and precipitation during the previous growing season. Spatial correlation and comparative analysis indicated that the P. tabuliformis chronology responded to extreme dry and wet events on a regional scale. Interannual and multidecadal periodic signals recorded by tree rings suggested that the hydrological and climatic changes on the southern slope of the central Qinling Mountains were teleconnected with the Pacific and Atlantic Oceans, including El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO). Our results provide new evidence for a hydroclimatical response study inferred from tree rings on the southern slope of the central Qinling Mountains.
“Let It Be” or “Nip It in the Bud”? A Study of the Impact of Population Outflow on Economic Growth and High-Quality Economic Development in Forest Areas
Authors: Liu Jiaqi , Cao Yukun , Li Jingye , Zhang Yafang
Published: January 2025

In the face of the realistic background of population loss, resource constraints and factor constraints, it explores the high-quality development of forest areas, aiming to analyze the impacts of population exodus from forest areas on economic growth and high-quality development. The focus is on China’s key state-owned forest areas, especially in Heilongjiang Province, Jilin Province and Inner Mongolia Autonomous Region. A set of indicators centered on the concept of green development is constructed and designed to measure the dynamics of high-quality economic development and the impact of population outflow in the three provinces and regions from 2000 to 2022. The study found that (1) Heilongjiang Province excels in high-quality economic development, followed by Jilin Province, while the Inner Mongolia Autonomous Region lags behind. During the observation period, the high-quality development trend in the forest areas showed a steady upward trend until 2014 and then began to slow down or even decline. (2) The pulling effect of population mobility on economic growth in forest areas has gradually weakened; nevertheless, the effective agglomeration of labor and capital is still a key factor driving economic growth. (3) Population exodus poses an obstacle to high-quality economic development. Increased population mobility has a negative impact on both economic growth and high-quality development, exacerbating economic fluctuations, and is not conducive to stability and high-quality development. It is worth noting that although the population base plays a fundamental role in economic growth, the direct effect of population on development is not significant. On the contrary, there is a negative correlation between population outflow and high-quality economic development. Based on the findings, strategic recommendations are made with the aim of promoting a shift from a growth model that relies on population numbers to a development model that focuses on the improvement of population quality in forest areas, thereby realizing a fundamental innovation in the economic development model. This study enriches the theory of regional development in forest areas and is of great significance in promoting sustainable development in forest areas.
A Novel Approach for the Counting of Wood Logs Using cGANs and Image Processing Techniques
Authors: Mazzochin João V. C. , Vitor Giovani Bernardes , Tiecker Gustavo , Diniz Elioenai M. F. , Oliveira Gilson A. , Trentin Marcelo , Rodrigues Érick O.
Published: January 2025

This study tackles the challenge of precise wood log counting, where applications of the proposed methodology can span from automated approaches for materials management, surveillance, and safety science to wood traffic monitoring, wood volume estimation, and others. We introduce an approach leveraging Conditional Generative Adversarial Networks (cGANs) for eucalyptus log segmentation in images, incorporating specialized image processing techniques to handle noise and intersections, coupled with the Connected Components Algorithm for efficient counting. To support this research, we created and made publicly available a comprehensive database of 466 images containing approximately 13,048 eucalyptus logs, which served for both training and validation purposes. Our method demonstrated robust performance, achieving an average Accuracypixel of 96.4% and Accuracylogs of 92.3%, with additional measures such as F1 scores ranging from 0.879 to 0.933 and IoU values between 0.784 and 0.875, further validating its effectiveness. The implementation proves to be efficient with an average processing time of 0.713 s per image on an NVIDIA T4 GPU, making it suitable for real-time applications. The practical implications of this method are significant for operational forestry, enabling more accurate inventory management, reducing human errors in manual counting, and optimizing resource allocation. Furthermore, the segmentation capabilities of the model provide a foundation for advanced applications such as eucalyptus stack volume estimation, contributing to a more comprehensive and refined analysis of forestry operations. The methodology’s success in handling complex scenarios, including intersecting logs and varying environmental conditions, positions it as a valuable tool for practical applications across related industrial sectors.
Lower Contents of Soil Organic Matter, Macro-Nutrients, and Trace Metal Elements in the Longleaf Pine Forests Restored from the Mixed Pine and Hardwood Forests
Authors: Chen Xiongwen
Published: January 2025

Restoration of the longleaf pine forest ecosystem is critical for biodiversity. However, the mixed hardwood forests can grow naturally in the same area. There are limited studies comparing soil organic matter and nutrient contents for restoring longleaf pine forests from the mixed hardwood forest areas in the southeastern USA. In this study, a comparison of the contents in soil organic matter, macro-nutrients, trace metal elements, and litterfall amount, was conducted on the 16 forest stands (4 treatments including stand stages × 4 replicants) at William B. Bankhead National Forest in Alabama through the space-replace-time approach. The results indicate that longleaf pine forests have lower contents of soil organic matter, macro-nutrients, most trace metal elements, and litterfall amount than mixed hardwood forests. However, longleaf pine forests have higher soil Ca, Ba, and Pb contents than hardwood forests. Soil Fe content has more correlations with the contents of other metal elements than soil Mn. The results suggest that multiple ecosystem functions, including soil ecology, must be considered in the regional restoration of the longleaf pine ecosystem. Longleaf pine forests with a certain amount of mixed hardwood trees may be a good way to maintain soil organic matter and nutrients.
Distribution of Starch in Trunkwood of Catalpa bungei ‘Jinsi’: A Revelation on the Metabolic Process of Energy Storage Substances
Authors: Zhao Xiping , Liu Fei , Guo Pingping , Feng Qi , Wang Dongfang , Hao Ziyuan
Published: January 2025

Starch is stored in thin-walled tissue of wood for several years or even decades. Starch reserves vary by anatomical structure, growth ring, and tree species. The spatial distribution pattern of starch in Catalpa bungei ‘Jinsi’ wood is unclear. We sampled three C. bungei ‘Jinsi’ trees at the end of the growing season and cut discs from their trunks to stain starch granules in wood ray cells with iodine–potassium iodide. We studied starch content in the ray cells of the trunks’ height position (stump, breast height, and crown base) from pith to bark in four directions (west, east, south, north) of the tree. There was a significant difference in starch content in three trunk height positions (p < 0.01), with stump (4.06 to 92.16%) > breast height (6.05 to 69.05%) > crown base (3.89 to 47.04%). There was a significant difference in starch content in different directions at the same height position. In the radial direction, the starch content of sapwood was much higher than that of heartwood, and the starch content showed an overall decreasing trend from bark to pith. The results indicated that starch distribution in tree trunks is uneven, which is related to energy metabolism processes, especially heartwood formation. This will contribute to further research on improving wood quality through the C. bungei ‘Jinsi’ tree breeding program.
Empirical Relationships of the Characteristics of Standing Trees with the Dynamic Modulus of Elasticity of Japanese Cedar (Cryptomeria japonica) Logs: Case Study in the Kyoto Prefecture
Authors: Harada Kiichi , Nakata Yasutaka , Nakazawa Masahiko , Kojiro Keisuke , Nagashima Keiko
Published: January 2025

With growing worldwide interest in constructing larger and taller wooden buildings, wood properties, such as the dynamic modulus of elasticity (MOEdyn), have become increasingly important. However, the MOEdyn of trees and logs has rarely been considered in forest management because a method for estimating the MOEdyn of logs based on standing tree characteristics has been lacking. Herein, we explored the multiple relationships between the MOEdyn of logs and standing tree characteristics of Japanese cedar (Cryptomeria japonica) such as tree height, diameter at breast height (DBH), and tree age, including the stress-wave velocity of the tree, which is known to be correlated with the MOEdyn of logs. The relationship between the MOEdyn of logs and standing tree characteristics was investigated by considering the bucking position. Different trends between the bottom logs and upper logs were found for all characteristics, showing a multiple trend of tree characteristics with the MOEdyn of logs based on the bucking position. The top three generalised linear mixed models for the prediction of the MOEdyn of logs showed relatively high accuracies when the bucking position was considered as a random effect. Although the contribution of the stress-wave velocity of the tree was relatively high, adding tree age improved the accuracy of the model, and this model was selected as the top model. The model for the bottom log, utilising the stress-wave velocity and age of the tree as explanatory variables, was highly explanatory (R2 = 0.70); however, the best model for upper logs was only moderately explanatory (R2 = 0.44). In addition, tree height and DBH were selected as explanatory variables along with tree age in the second and third models, which suggested the importance of growth rate rather than tree size. Therefore, adding correlates associated to characteristics related to height growth, such as site index, and DBH growth, such as stand density, is expected to improve model accuracy.
Transonic Aerodynamic Performance Analysis of a CRM Joined-Wing Configuration
Authors: Hanman Paul , Yao Yufeng , Bouferrouk Abdessalem
Published: January 2025

This study examines the aerodynamic performance of a joined-wing (JW) aircraft design based on the NASA Common Research Model (CRM), aiming to assess its potential for efficient commercial transport or cargo aircraft at transonic speed (Mach 0.85). The CRM wing, optimised for transonic flight, was transformed into a JW design featuring a high-aspect-ratio main wing. An initial parametric study using the vortex lattice minimum drag panel method identified viable designs. The selected JW configuration, comprising front and rear wings joined by a vertical fin, was analysed using ANSYS Fluent to understand flow interactions and aerodynamic performance. At an angle of attack (AoA) of −1°, the JW design achieved a peak lift-to-drag ratio (L/D) of 17.45, close to the CRM’s peak L/D of 19.64 at 2°, demonstrating competitive efficiency. The JW’s L/D exceeded the CRM’s between AoA −3° and 0.8°, but the CRM performed better above 0.8°, with differences decreasing at a higher AoA. Based on induced drag alone, the JW outperformed the CRM across AoA −3° to 8°, but flow complications restricted its L/D advantage to a small, low AoA range. A strong shock on the vertical fin’s inboard side due to high incoming flow speed delayed shock formation on the main wing near the joint. Optimising the vertical fin shape slightly improved L/D, suggesting potential for further enhancements or that other design factors significantly affect JW performance. This study provides insights into JW aerodynamics at transonic speeds, revealing its potential benefits and challenges compared to the CRM design.
Features of Supersonic Flow Around a Blunt Body in the Area of Junction with a Flat Surface
Authors: Lapushkina T. A. , Kolesnik E. V. , Monahov N. A. , Popov P. A. , Belov K. I.
Published: January 2025

This work studies the influence of a growing boundary layer on the process of supersonic flow around an aerodynamic body. The task is to select and implement in an experiment the parameters of a supersonic flow and to study the flow pattern near the surface of an aerodynamic body at different viscosity values for the incoming flow. Visualization of the shock wave configuration in front of the body and studying the change in the pressure field in the flow region under these conditions is the main goal of this work. The experiment was carried out on an experimental stand created on the basis of a shock tube. The aerodynamic body under study (a semi-cylinder pointed along a circle or an ellipse) was placed in a supersonic nozzle. The model was clamped by lateral transparent walls, which were simultaneously a source of boundary layer growth and the viewing windows for visualizing the flow. For selected modes with Reynolds numbers from 8200 to 45,000, schlieren flow patterns and pressure distribution fields near the surface of the streamlined models and the plate of the growing boundary layer were obtained. The data show a complex, unsteady flow pattern realized near the model which was caused by the viscous-inviscid interaction of the boundary layer with the bow shock wave near the wall.
Antioxidant Peptides from Hizikia fusiformis: A Study of the Preparation, Identification, Molecular Docking, and Cytoprotective Function of H2O2-Damaged A549 Cells by Regulating the Keap1/Nrf2 Pathway
Authors: Lv Shang , Hu Bin , Ran Su-Zhen , Zhang Min , Chi Chang-Feng , Wang Bin
Published: January 2025

Hijiki (Hizikia fusiformis) is a seaweed native to warm-temperate and subtropical regions that has a high edible value and economic value, with a production of about 2 × 105 tons/year. Current research has clearly shown that the pharmacological activities of active ingredients from hijiki have covered a broad spectrum of areas, including antioxidant, hypoglycemic, antiviral, anticoagulant, anti-inflammatory, intestinal flora modulation, anti-aging, antineoplastic and antibacterial, and anti-Alzheimer’s disease areas. However, no studies have reported on the production of antioxidant peptides from hijiki proteins. The objectives of this study were to optimize the preparation process and explore the cytoprotective function and mechanisms of antioxidant peptides from hijiki protein. The results indicated that papain is more suitable for hydrolyzing hijiki protein than pepsin, trypsin, alkaline protease, and neutral protease. Under the optimized parameters of an enzyme dosage of 3%, a material–liquid ratio of 1:30, and an enzyme digestion time of 5 h, hijiki hydrolysate with a high radical scavenging activity was generated. Using ultrafiltration and serial chromatographic methods, ten antioxidant oligopeptides were purified from the papain-prepared hydrolysate and identified as DGPD, TIPEE, TYRPG, YTPAP, MPW, YPSKPT, YGALT, YTLLQ, FGYGP, and FGYPA with molecular weights of 402.35, 587.61, 592.64, 547.60, 532.53, 691.77, 523.57, 636.73, 539.58, and 553.60 Da, respectively. Among them, tripeptide MPW could regulate the Keap1/Nrf2 pathway to significantly ameliorate H2O2-induced oxidative damage of A549 cells by increasing cell viability and antioxidant enzyme (SOD, CAT, and GSH-Px) activity, decreasing ROS and MDA levels, and reducing the apoptosis rate. Molecular docking experiments show that HFP5 (MPW) exerts its inhibitory effect mainly through hydrogen bonds and hydrophobic interactions with the Kelch domain of the Keap1 protein, eventually facilitating the translocation of Nrf2 to the nucleus. Therefore, antioxidant peptides from hijiki can be applied to develop algae-derived health foods for treating diseases associated with oxidative stress.
Synergistic Anti-Helicobacter pylori Effects of Takifugu obscurus Skin Peptides and Lactobacillus plantarum: A Potential Gastric Health Dietary Supplement
Authors: Gu Lei , Tang Yiying , Zhang Jieshuai , Tao Ningping , Wang Xichang , Wang Liping , Xu Changhua
Published: January 2025

Helicobacter pylori (H. pylori) infection is a widespread gastric infectious disease, posing significant challenges due to the increasing prevalence of antibiotic resistance. This study aimed to evaluate the synergistic antibacterial activity of Takifugu obscurus skin peptides (TSPs) and the cell-free supernatant of Lactobacillus plantarum WUH3 (LCFS) in developing a potential green and efficient dietary supplement therapy. Using enzymatic hydrolysis and ultrafiltration techniques, the most bioactive peptide fraction, TSPb (1–3 kDa), was identified. The effects of TSPb and LCFS—both individually and in combination—on H. pylori biofilm function, membrane morphology, and internal structure were systematically analyzed using urease activity, N-phenyl naphthylamine (NPN) uptake, nucleic acid leakage, scanning electron microscopy (SEM), and infrared (IR) spectroscopy. The results showed that both LCFS and TSPb significantly inhibited H. pylori urease activity, with inhibition rates of 53.60% and 54.21% at 24 h, respectively, and the highest inhibition rate of 74.64% was observed with their combined treatment. SEM, NPN fluorescence, and nucleic acid leakage analyses revealed distinct mechanisms of action for each treatment. LCFS treatment caused membrane surface loosening and morphological deformation, while TSPb induced the formation of localized membrane pores. IR spectroscopy further confirmed that the combined treatment led to a more severe disruption of the lipid and protein structure within the bacterium. Overall, compared to individual treatments, the combination of TSPb and LCFS exhibited enhanced intracellular penetration and a more significant effect on bacterial viability. This study successfully identified TSPb as a highly bioactive peptide and elucidated its potential synergistic antibacterial mechanism with LCFS. These findings provide scientific evidence for the development of functional antimicrobial foods and gastric health dietary supplements, offering a promising strategy for the prevention and management of H. pylori infections.
Lacticaseibacillus casei JS-2 from ‘Jiangshui’ Reduces Uric Acid and Modulates Gut Microbiota in Hyperuricemia
Authors: Wu Jiahui , Wang Xiang , Aga Lvbu , Tang Leimengyuan , Tan Shuting , Zhang Dachuan , Li Houxier , Yang Li , Zhang Nan , Su Shiyao , Xiao Maochun , Min Rongting , Li Aji , Wang Xueyong
Published: January 2025

Lacticaseibacillus casei (JS-2) is a novel probiotic isolated from “Jiangshui”, a kind of traditional folk fermented food, which has a significant effect on hyperuricemia (HUA). In vitro experimental results showed that JS-2 has a high degradation ability and selectivity for uric acid (UA). The animal test results indicated that after two weeks of treatment, JS-2 could significantly reduce the level of UA in the serum of HUA quails (p < 0.01), and its effect is almost equivalent to that of the positive drug control group, benzbromarone. Further, after JS-2 treatment, the level of xanthine oxidase in quail serum decreased significantly. Analysis data of quail fecal metabolomics results showed that JS-2-altering metabolites were involved in amino acid, purine, and lipid metabolism. To investigate the mechanism underlying JS-2-mediated UA degradation in the quail model of HUA, 16S rRNA gene sequencing was conducted. It was found that the structure and function of the gut microbiota were restored after JS-2 intervention, and the abundance of short-chain fatty acid (SCFA)-producing bacteria (g__Ruminococcus_torques_group and g__Butyricicoccus) and bacteria with UA degradation capacity (g__unclassified_f__Lachnospiraceae and g__Negativibacillus) increased significantly; intestinal SCFAs, especially propionic acid, increased accordingly. These experimental data suggest that the beneficial effects of JS-2 may derive from changes in the gut microbiome, altering host–microbiota interactions, reducing UA levels by increasing UA excretion, and reducing absorption. These findings provided new evidence that JS-2 has the potential to be used as a naturally functional food for the prevention of HUA.
Transcriptomic Characterization of miRNAs in Apis cerana Larvae Responding to Ascosphaera apis Infection
Authors: Song Yuxuan , Qiu Jianfeng , Kang Jing , Chen Ying , Cao Ruihua , Wang Wei , Dai Mengyuan , Chen Dafu , Fu Zhongmin , Guo Rui
Published: January 2025

Ascosphaera apis is a fungal pathogen that specifically infects bee larvae, causing an outbreak of chalkbrood disease in the bee colony and a decline in the number of bee colonies. The role of miRNA regulation in honeybees in response to A. apis infection is unclear. In this study, based on small RNA-seq, we identified the differentially expressed miRNAs (DEmiRNAs) and their regulatory networks and functions in the gut of Apis cerana cerana on the first day (AcT1), the second day (AcT2) and the third day (AcT3) after A. apis infection, and analyzed the immune response mechanism of A. apis through the miRNAs-mRNA regulation network of A. apis infection. A total of 537 miRNAs were obtained, and 10, 27, and 54 DEmiRNAs were screened in the AcT1, AcT2, and AcT3 groups, respectively. The number of DEmiRNAs gradually increased with the infection time. Stem-loop RT-PCR results showed that most of the DEmiRNAs were truly expressed, and the expression trend of DEmiRNAs was consistent with the results of sRNA-seq. The top five GO terms of DEmiRNA-targeted mRNA were binding, cellular process, catalytic activity, metabolic process, and single-organism process. The main pathways enriched by KEGG were endocytosis, ubiquitin-mediated proteolysis, phagosome, and the JAK-STAT immune-related signaling pathways. The number of DEmiRNAs and target mRNAs of these related pathway genes increased with infection time. The miRNA-mRNA regulatory network analysis showed that ace-miR-539-y was the core miRNA of the early immune response in the gut of larvae infected with A. apis in the JAK-STAT pathway and phagosome, and ace-miR-1277-x was the core miRNA of the late immune response in the gut of larvae infected with A. apis in the JAK-STAT signaling pathway and phagosome. The results showed that miRNA participated in the immune response of honeybees to A. apis infection by regulating the host’s energy metabolism, cellular immunity, and humoral immunity. The results of this study provide a basis for the regulation of miRNAs in A. c. cerana larvae in response to A. apis infection and provide new insights into host-pathogen interactions.
The Association of Genetic Variants Within the Type XII Collagen and Tenascin C Genes with Knee Joint Laxity Measurements
Authors: Beckley Samantha , Dey Roopam , Stinton Shaun , van der Merwe Willem , Branch Thomas , September Alison V. , Posthumus Michael , Collins Malcolm
Published: January 2025

Background/Objectives: Types I, V, and XI collagen gene variants have been reported to associate with measurements of knee joint laxity and/or absolute knee ligament length changes. Type XII collagen and tenascin C are also ligament structural proteins whose expression is regulated by mechanical loading. This study investigated whether COL12A1 and TNC variants are associated with knee laxity and/or ligament length changes. Methods: Genu recurvatum, anterior–posterior tibial translation, external–internal tibial rotation, and ligament length changes were measured in 128 healthy participants. They were genotyped for COL12A1 (rs970547) and TNC (rs1061494, rs2104772, rs1138545). Results: Both the COL12A1 AA and TNC rs1061494 TT genotypes were associated with decreased external (p = 0.007, p = 0.010) and internal (p = 0.025, p = 0.002) rotation, as well as slack (p = 0.033, p = 0.014), in the dominant leg. Both genotypes, together with sex, weight, and/or COL1A1 genotypes, explained 26% and 32% of the variance in external and internal rotation, respectively. The TNC genotype, sex, and BMI explained 23% of the variance in slack. The COL12A1 AA and the TNC rs1061494 TT genotypes were associated with smaller changes in the MCL (aMCL: COL12A1 p = 0.009, TNC p = 0.045; iMCL: COL12A1 p = 0.004, TNC p = 0.043; pMCL: COL12A1 p = 0.003, TNC p = 0.067; aDMCL: COL12A1 p = 0.007, TNC p = 0.020; pDMCL: COL12A1 p = 0.007, TNC p = 0.023) and/or LCL (COL12A1 p = 0.652, TNC p = 0.049) lengths within the dominant knee. The TNC rs1061494 CC genotype was associated with larger changes in the non-dominant anterior (p = 0.021) and posterior (p < 0.001) ACL bundle lengths. Conclusions: These findings suggest that COL12A1 and TNC variants are associated with internal–external tibial rotation and knee ligament length changes in healthy individuals.