bluuebunny/crossref_metadata_2025 huggingface dataset:
KLR-KGC: Knowledge-Guided LLM Reasoning for Knowledge Graph Completion
Authors: Ji Shengwei , Liu Longfei , Xi Jizhong , Zhang Xiaoxue , Li Xinlu
Published: December 2024

Knowledge graph completion (KGC) involves inferring missing entities or relationships within a knowledge graph, playing a crucial role across various domains, including intelligent question answering, recommendation systems, and dialogue systems. Traditional knowledge graph embedding (KGE) methods have proven effective in utilizing structured data and relationships. However, these methods often overlook the vast amounts of unstructured data and the complex reasoning capabilities required to handle ambiguous queries or rare entities. Recently, the rapid development of large language models (LLMs) has demonstrated exceptional potential in text comprehension and contextual reasoning, offering new prospects for KGC tasks. By using traditional KGE to capture the structural information of entities and relations to generate candidate entities and then reranking them with a generative LLM, the output of the LLM can be constrained to improve reliability. Despite this, new challenges, such as omissions and incorrect responses, arise during the ranking process. To address these issues, a knowledge-guided LLM reasoning for knowledge graph completion (KLR-KGC) framework is proposed. This model retrieves two types of knowledge from the knowledge graph—analogical knowledge and subgraph knowledge—to enhance the LLM’s logical reasoning ability for specific tasks while injecting relevant additional knowledge. By integrating a chain-of-thought (CoT) prompting strategy, the model guides the LLM to filter and rerank candidate entities, constraining its output to reduce omissions and incorrect responses. The framework aims to learn and uncover the latent correspondences between entities, guiding the LLM to make reasonable inferences based on supplementary knowledge for more accurate predictions. The experimental results demonstrate that on the FB15k-237 dataset, KLR-KGC outperformed the entity generation model (CompGCN), achieving a 4.8% improvement in MRR and a 5.8% improvement in Hits@1.
A Review of Large Language Models: Fundamental Architectures, Key Technological Evolutions, Interdisciplinary Technologies Integration, Optimization and Compression Techniques, Applications, and Challenges
Authors: Han Songyue , Wang Mingyu , Zhang Jialong , Li Dongdong , Duan Junhong
Published: December 2024

Large language model-related technologies have shown astonishing potential in tasks such as machine translation, text generation, logical reasoning, task planning, and multimodal alignment. Consequently, their applications have continuously expanded from natural language processing to computer vision, scientific computing, and other vertical industry fields. This rapid surge in research work in a short period poses significant challenges for researchers to comprehensively grasp the research dynamics, understand key technologies, and develop applications in the field. To address this, this paper provides a comprehensive review of research on large language models. First, it organizes and reviews the research background and current status, clarifying the definition of large language models in both Chinese and English communities. Second, it analyzes the mainstream infrastructure of large language models and briefly introduces the key technologies and optimization methods that support them. Then, it conducts a detailed review of the intersections between large language models and interdisciplinary technologies such as contrastive learning, knowledge enhancement, retrieval enhancement, hallucination dissolution, recommendation systems, reinforcement learning, multimodal large models, and agents, pointing out valuable research ideas. Finally, it organizes the deployment and industry applications of large language models, identifies the limitations and challenges they face, and provides an outlook on future research directions. Our review paper aims not only to provide systematic research but also to focus on the integration of large language models with interdisciplinary technologies, hoping to provide ideas and inspiration for researchers to carry out industry applications and the secondary development of large language models.
FedSparse: A Communication-Efficient Federated Learning Framework Based on Sparse Updates
Authors: Li Jiachen , Zhang Yuchao , Li Yiping , Gong Xiangyang , Wang Wendong
Published: December 2024

Federated learning (FL) strikes a balance between privacy preservation and collaborative model training. However, the periodic transmission of model updates or parameters from each client to the federated server incurs substantial communication overhead, especially for participants with limited network bandwidth. This overhead significantly hampers the practical applicability of FL in real-world scenarios. To address this challenge, we propose FedSparse, an innovative sparse communication framework designed to enhance communication efficiency. The core idea behind FedSparse is to introduce a communication overhead regularization term into the client’s objective function, thereby reducing the number of parameters that need to be transmitted. FedSparse incorporates a Resource Optimization Proximal (ROP) term and an Importance-based Regularization Weighting (IRW) mechanism into the client update objective function. The local update process optimizes both the empirical risk and communication overhead by applying a sparse regularization weighted by update importance. By making minimal modifications to traditional FL approaches, FedSparse effectively reduces the number of parameters transmitted, thereby decreasing the communication overhead. We evaluate the effectiveness of FedSparse through experiments on various datasets under non-independent and identically distributed (non-IID) conditions, demonstrating its flexibility in resource-constrained environments. On the MNIST, Fashion-MNIST, and CIFAR datasets, FedSparse reduces the communication overhead by 24%, 17%, and 5%, respectively, compared to the baseline algorithm, while maintaining similar model performance. Additionally, on simulated non-IID datasets, FedSparse achieves a 6% to 8% reduction in communication resource consumption. By adjusting the sparsity intensity hyperparameter, we demonstrate that FedSparse can be tailored to different FL applications with varying communication resource constraints. Finally, ablation studies highlight the individual contributions of the ROP and IRW modules to the overall improvement in communication efficiency.
DEVS-Based CDC Synchronizer Design for Fast Debugging of Metastability
Authors: Kwon Bo Seung , Han Young Shin , Lee Jong Sik
Published: December 2024

This paper proposes a DEVS (Discrete Event System Specification) formalism-based approach to analyze Clock Domain Crossing (CDC) issues in digital circuit design. As modern System on Chip (SoC) designs increasingly integrate multiple clock domains, the verification of CDC-related metastability becomes more challenging and costly. While conventional EDA tools offer solutions for CDC analysis, they often involve substantial computational resources and licensing costs. We present a DEVS-based simulation framework that leverages its inherent advantages in time management and modular structuring to model and analyze CDC scenarios. The framework includes a CDC synchronizer model implemented within the HDL partially compatible DEVS environment, enabling precise analysis of metastability violations based on setup time and hold time requirements. Circuit designers or related engineers can potentially solve timing issues such as CDC by incorporating DEVS-based analysis tools into the design pipeline.
Unleashing the Potential of Permissioned Blockchain: Addressing Privacy, Security, and Interoperability Concerns in Healthcare Data Management
Authors: Hossain Delowar , Mamun Quazi , Islam Rafiqul
Published: December 2024

Blockchain technology leverages a cryptographic system to provide secure and immutable storage of transaction histories within a decentralised framework. While various industries have demonstrated interest in integrating blockchain into their IT systems, concerns regarding accessibility, privacy, performance, and scalability persist. Permissioned blockchain frameworks offer a viable solution for securing confidential records. Extensive research has been conducted to explore the opportunities, challenges, application areas, and performance evaluations of different public and permissioned blockchain platforms. Given the sensitive nature of medical information, healthcare organisations must adhere to various legal obligations, including HIPAA regulations, to protect these data. Although navigating these requirements can be challenging, it is crucial for safeguarding the reputation of healthcare providers, maintaining patient trust, and avoiding legal repercussions. Permissioned blockchains represent decentralised digital ledgers tailored to collaborate among businesses and organisations. Their popularity has increased significantly in recent years, resulting in the availability of several leading options, such as Hyperledger Fabric, Corda, Quorum, and MultiChain. Each of these platforms presents its own set of advantages and disadvantages. Although blockchain technology remains relatively nascent in the permissioned realm, several factors warrant consideration when comparing these platforms. This study will review the existing landscape of blockchain technologies in healthcare applications and identify the research scopes. This research aims to determine how permissioned blockchain technology can effectively fulfil the requirements for managing healthcare data.
Large-Bandwidth Lithium Niobate Electro-Optic Modulator for Frequency-Division Multiplexing RFID Systems
Authors: Luo Xueting , Gu Zhenqian , Wang Chong , Fan Chao , Zhang Weijia
Published: December 2024

In the face of increasingly complex application scenarios, there is an urgent need for (Radio Frequency Identification) RFID systems that are capable of accurately identifying microwave signals of different frequency bands. Based on the acumen detection characteristics of microwave signals by lithium niobate electro-optic modulators, applying large-bandwidth thin-film lithium niobate electro-optic modulation to RFID systems can achieve efficient operation across multiple frequency bands. This study discusses, in detail, the design, simulation, fabrication, and testing process of the electro-optic modulator to obtain a high-performance, large-bandwidth lithium niobate electro-optic modulator. By using multilayer lithography techniques to prepare thick traveling-wave electrodes, the problem of irregular cross-sections during the fabrication of thick electrodes has been successfully reduced, improving the stability and controllability of the device. Test results show that the insertion loss of the electro-optic modulator is about 6 dB, the extinction ratio is 36.5 dB, the optical waveguide mode field is 1 μm, the full-band characteristic impedance is 50 Ω, the test bandwidth is 50 GHz, and the half-wave voltage is 1.8 V. Compared with existing optimization schemes, this design not only achieves a large bandwidth and a small half-wave voltage, but also proposes a new fabrication process scheme, optimizing the process and resulting in samples with stable performance.
Boosted Equilibrium Optimizer Using New Adaptive Search and Update Strategies for Solving Global Optimization Problems
Authors: Tuna Resul , Çelik Yüksel , Fındık Oğuz
Published: December 2024

The Equilibrium Optimizer (EO) is an optimization algorithm inspired by a physical law called mass balance, which represents the amount of mass entering, leaving, and being produced in a control volume. Although the EO is a well-accepted and successful algorithm in the literature, it needs improvements in the search, exploration, and exploitation phases. Its main problems include low convergence, getting stuck in local minima, and imbalance between the exploration and exploitation phases. This paper introduces the Boosted Equilibrium Optimizer (BEO) algorithm, where improvements are proposed to solve these problems and improve the performance of the EO algorithm. New methods are proposed for the three important phases of the algorithm: initial population, candidate pool generation, and updating. In the proposed algorithm, the exploration phase is strengthened by using a uniformly distributed random initial population instead of the traditional random initial population and a versatile concentration pool strategy. Furthermore, the balance between the exploration and exploitation phases is improved with two new approaches proposed for the updating phase. These novel methods enhance the algorithm’s performance by more effectively balancing exploration and exploitation. The proposed algorithm is tested using a total of 23 standard test functions, including unimodal, multimodal, and fixed-size multimodal. The results are supported by numerical values and graphs. In addition, the proposed BEO algorithm is applied to solve real-world engineering design problems. The BEO outperforms the original EO algorithm on all problems.
High-Energy-Density Hydrochar and Bio-Oil from Hydrothermal Processing of Spent Coffee Grounds—Experimental Investigation
Authors: Wądrzyk Mariusz , Katerla Jakub , Janus Rafał , Lewandowski Marek , Plata Marek , Korzeniowski Łukasz
Published: December 2024

Spent coffee grounds (SCGs), a by-product of coffee brewing, have high application potential. However, their high moisture content complicates conventional conversion without energy-intensive drying. This study explores a new route to convert SCGs to high-carbon bioproducts, such as hydrochar and bio-oil, through hydrothermal processing. The effect of the processing variables, i.e., temperature, residence time, and the application of the binary solvent as a reaction medium, on the distribution of the resultant bioproducts was investigated. The quality of the fabricated bioproducts was analyzed by means of instrumental techniques such as EA, ATR-FTIR, GC-MS, and GC-TCD-FID. Two dominant fractions were liquid bio-oil and solid hydrochar. The highest char yield (39 wt.%) was observed under milder conditions (low T and short residence times), while more severe conditions led to an increase in bio-oil formation, which reached a maximum of 46 wt.%. The resulting bio-oils were of similar quality, presenting high carbon content (71–74 wt.%) and energetic values (approximately 35 MJ/kg). Also, hydrochars showed a noticeable energy densification compared to raw materials, where the C content and HHV reached up to 73.8 wt.% and 30 MJ/kg, respectively. The addition of co-solvent to water improves the bio-oil yield as a result of the enhanced stabilization of reactive intermediates.
Injected Fuel Mass and Flow Rate Control in Internal Combustion Engines: A Systematic Literature Review
Authors: Ferrari Alessandro , Gurrì Simona , Vento Oscar
Published: December 2024

Advancements in fuel injection systems have dramatically improved the precision of controlling injected fuel mass or flow rate; a key factor in optimizing internal combustion engine (ICE) performance, emissions control, and fuel efficiency. This review systematically analyzes 145 scientific research papers from the last two decades, including older foundational works, tracing the evolution of injected mass control from early Bosch and Zeuch meters to advanced machine learning or physical models. This study draws upon research collected from the most reputable databases. Through both qualitative and quantitative analyses, the state-of-the-art of these systems is presented, and key innovations are highlighted regarding advanced control algorithms and real-time feedback mechanisms under various operational conditions such as high or transient loads and multi-stage injection strategies. Special attention is given to challenges in maintaining precise control with alternative fuels like biodiesel, hydrogen, or synthetic fuels, which exhibit different physical properties compared to traditional fuels. The findings emphasize the need for further research on injection control, especially in light of stringent emissions regulations. Improving these systems for next-generation ICEs is a key point for achieving cleaner, more efficient combustion and bridging the sustainability gap between traditional and future mobility solutions.
Thermophysical Modeling of the Vaporization Process in a Motive Nozzle with a Profiled Supersonic Part
Authors: Sharapov Serhii , Husiev Danylo , Klymenko Volodymyr , Pavlenko Ivan , Ginter-Kramarczyk Dobrochna , Krupińska Andżelika , Ochowiak Marek , Włodarczak Sylwia
Published: December 2024

In this article, thermophysical modeling of boiling flows in the motive nozzle is carried out for a liquid–vapor jet apparatus (LVJA). Existing thermophysical models make it possible to calculate nozzles, which, in their shape, are close to Laval nozzles. They also allow for determining the position of the outlet cross-sectional area of the nozzle, where the flow separation from the channel walls occurs. However, these models do not allow for profiling the nozzle’s supersonic part, which does not make it possible to ensure the maximum efficiency of the vaporization process. Therefore, in the presented article, the available thermophysical model was improved significantly, which made it possible to obtain the profile of the supersonic part of the nozzle. As a result, a geometric shape that ensures the highest efficiency of the outflow process can be chosen for the primary flow at specified initial and final thermodynamic parameters. According to the calculation results and the proposed methodology, parameters were distributed along the nozzle for the primary flow. Also, efficiency indicators of the outflow of the boiling liquid underheated to saturation were achieved for the different geometric shapes. Mathematical modeling of the operating process in the motive nozzle using ANSYS CFX 2004 R1 (ANSYS, Inc., Canonsburg, PA, USA) was performed to prove the reliability of the results. Also, a comparative analysis of the obtained calculation and simulation results for nozzles with a profiled supersonic part and straight walls was carried out. To assess the expediency of profiling the supersonic part of the nozzle for the primary flow at the LVJA, a comparison of analytical modeling and numerical simulation results with the experimental studies was carried out for nozzles with straight walls. Finally, the velocity ratios of nozzles with profiled supersonic parts and straight walls were obtained. This allowed for rational choosing of the nozzle shape to ensure the highest vaporization efficiency.
A Deep-Neural-Network-Based Surrogate Model for DC/AC Converter Topology Selection Using Multi-Domain Simulations
Authors: Avila Saccol Gabriel , Bui Van-Hai , Su Wencong
Published: December 2024

The selection of optimal DC/AC power converter topologies for specific applications is often a time-consuming and complex task, which can lead to suboptimal choices. This paper proposes an AI-assisted methodology to identify the most efficient DC/AC converter based on a set of input design parameters. Separate deep-neural-network-based surrogate models are developed for each considered topology, trained by a large dataset of simulation results obtained from MATLAB/Simulink and PSIM, so that the efficiency of each converter can be determined without performing additional simulations. The proposed methodology allows for quick and accurate efficiency estimation, significantly reducing the analysis time for topology selection. A case study for the two-level converter is also presented, demonstrating that additional parameters, such as the semiconductors junction temperature and output current distortion, can also be predicted using a similar methodology. Results are presented to demonstrate the feasibility of the proposed method.
Investigation of Hydrogen Transport Behavior in Polyethylene Terephthalate Membrane by Prolonged Hydrogen Exposure Treatments
Authors: Abdullayev Elman , Fladung Thorsten , Noeske Paul-Ludwig Michael , Mayer Bernd
Published: December 2024

Polyethylene terephthalate (PET) is one of the most used polymeric substances in production of packaging materials, fibers, textiles, coatings, and engineering materials. This paper elucidates the transport parameters of hydrogen gas through a PET membrane, which was selected to be a sufficiently permeable substrate for setting up an empirical strategy that aims at developing hydrogen barrier coatings. An examination of the structural degradation of PET by prolonged hydrogen exposure was performed. Hydrogen permeation tests were performed on a PET membrane with a thickness of 50 μm. To investigate the behavior of the material by prolonged hydrogen treatment, hydrogen-exposure experiments were carried out at a certain hydrogen pressure and time. Comparisons of the mechanical properties of the material were documented both before and after hydrogen exposure. A strong impact of comparatively transient hydrogen exposure on the mechanical and hydrogen transport properties of PET was observed. After 72 h of hydrogen exposure at 103 hPa and 300 K, the tensile strength decreased by 19%, the diffusion coefficients more than doubled, and material fracture behavior changed from ductile to distinctly brittle. This underlines the importance of developing effective hydrogen barrier coatings in case PET tubing is intended for use in hydrogen transport or storage.
Aerodynamic Effect of Winglet on NREL Phase VI Wind Turbine Blade
Authors: Huque Ziaul , Chowdhury Mahmood Sabria , Lu Haidong , Kommalapati Raghava Rao
Published: December 2024

The primary goal in designing wind turbine blades is to maximize aerodynamic efficiency. One promising approach to achieve this is by modifying the blade geometry, with winglets to the tip. Winglets are intended to reduce the strength of the tip vortices, thereby reducing induced drag, increasing torque, and, ultimately, improving the power output of the wind turbines. In this study, computational fluid dynamics (CFD) simulations were utilized to assess the aerodynamic performance of wind turbine blades with and without winglets at various wind speeds (5, 7, 10, 13, 15, 20, and 25 m/s). The results indicate that winglets have a limited effect at low (5 and 7 m/s) and high (20 and 25 m/s) wind speeds due to fully attached and separated flows over the blade surface. However, within the 10–15 m/s range, winglets significantly enhance torque and power output. While this increased power generation is beneficial, it is essential to consider the potential impact of the associated increase in thrust force on turbine stability.
Catalyst-Free Depolymerization of Methanol-Fractionated Kraft Lignin to Aromatic Monomers in Supercritical Methanol
Authors: Ghosh Shubho , Rana Masud , Park Jeong-Hun
Published: December 2024

Lignin is considered a renewable source for the production of valuable aromatic chemicals and liquid fuel. Solvent depolymerization of lignin is a fruitful strategy for the valorization of lignin. However, Kraft lignin is highly prone to produce char (a by-product) during the hydrothermal depolymerization process due to its poor solubility in organic solvents. Therefore, the minimization of char formation remains challenging. The purpose of the present study was to fractionate Kraft lignin in methanol to obtain low-molecular-weight fractions that could be further depolymerized in supercritical methanol to produce aromatic monomers and to suppress char formation. The results showed that the use of methanol-soluble lignin achieved a bio-oil yield of 45.04% and a char yield of 39.6% at 280 °C for 2 h compared to 28.57% and 57.73%, respectively, when using raw Kraft lignin. Elemental analysis revealed a high heating value of 30.13 MJ kg−1 and a sulfur content of only 0.09% for the bio-oil derived from methanol-soluble lignin. The methanol extraction process reduced the oxygen content and increased the hydrogen and carbon contents in the modified lignin and bio-oil, indicating that the extracted lignin fraction had an enhanced deoxygenation capability and a higher energy content. These findings highlight the potential of methanol-soluble Kraft lignin as a valuable resource for sustainable energy production and the production of aromatic compounds.
The Effect of the Vaccinium myrtillus L. Rhizosphere on the Maturity Index for Predatory Mites (Mesostigmata: Gamasina) in Assessing Anthropogenic Pollution of Forest Soils
Authors: Barczyk Gabriela , Nadgórska-Socha Aleksandra , Kandziora-Ciupa Marta
Published: December 2024

The soil’s biological quality and its functions are closely linked. They determine the ecological processes and ecosystem services. Therefore, the heavy metal contamination of forest soils, leading to their degradation, is a major international problem. Soil is a habitat for many organisms, and the strong correlations between soil properties, vegetation, and soil fauna are particularly evident in the rhizosphere. Therefore, comprehensive soil monitoring must take all these elements into account. In forest soils, Vaccinium myrtillus plays a vital role. Despite this, there is still a lack of information in the literature on the interrelationship between microarthropod biodiversity, including predatory soil mites, and heavy metals in the rhizosphere zone of blueberry plants. To fill this gap, we assessed the impact of the V. myrtillus rhizosphere on soil stability and biological quality using a bioindicator based on predatory mites. We conducted the study in Poland, on selected forest sites characterised by varying degrees of soil contamination. In our study, we used a combined analysis based on the following indicators: maturity index (MI), contamination factor (CF), pollution load index (PLI), and potential ecological risk index (PERI), which allowed us to determine the level of soil contamination. We extracted 4190 Gamasina mites from soil samples. We also investigated soil properties such as pH, organic matter content, total carbon, total nitrogen, C/N ratio, and heavy metal concentrations (Cd, Cu, Zn, Pb, and Ni). Our study proved that the rhizosphere zone significantly influences the stability of the predatory soil mite community, but this influence depends on the degree of soil contamination. We found that in unpolluted or moderately polluted soil, soil mites prefer habitats with less biological activity, i.e., non-rhizosphere zones. These main results are fascinating and indicate the need for further in-depth research. Our study’s comprehensive combination of methods provides valuable information that can facilitate the interpretation of environmental results. In addition, our study can be a starting point for analysing the impact of the rhizosphere zones of many other plant species, especially those used in the reclamation or urban spaces.
Sequoia Groves of Yosemite: Visitor Use and Impact Monitoring
Authors: Shiflett Sheri A. , Jenkins Jeffrey S. , Mattos Rachel F. , Ibsen Peter C. , Athearn Nicole D.
Published: December 2024

Despite being long-lived and massive, giant sequoias (Sequoiadendron giganteum (Lindl.) J. Bucholz) are susceptible to erosion given their relatively shallow root structure. Human-caused soil compaction and vegetation loss through social trails are primary drivers of erosion in giant sequoia groves, particularly for trees that are near formal trails and access roads. We develop a method to observe and quantify the near-tree impacts from park visitors and to relate the overall amount of use with ground cover impact parameters to assess whether the desired conditions of each grove are being met for the park to maintain a spectrum of recreational opportunities. We collected data on visitation, ground cover, soil compaction, and social trailing using a combination of targeted surveys and observations at the three giant sequoia groves in Yosemite National Park. The Mariposa Grove receives the most visitation, and use levels among groves were consistent with relative size and facilities available. Selected parameters for ground cover data were analyzed by comparing values within undisturbed versus trampling-disturbed subplots at both 0–2 m and 2–8 m. Exposed soil cover and compaction were generally higher in anthropogenically disturbed subplots versus undisturbed subplots, and vegetation cover was reduced in some disturbed subplots. Each grove had one surveyed tree where average soil compaction was ≥2.2 kg/cm2, which may limit root growth and impact seedling regeneration. Each of the three groves had some trees with social trail presence, yet less than 7% of mature trees within any grove were impacted by social trails, and most social trails were rated as having low impairment. Coupling soil compaction measurements and estimates of trampling-disturbed areas with mapping of social trail conditions within groves provides a general assessment of visitor-associated impacts to sequoia groves and can facilitate a relatively rapid way to track hotspot (i.e., increasingly impacted) trees over time.
Is the Level of Quality of Life Related to the Frequency of Visits to Natural Areas?
Authors: Korcz Natalia , Kamińska Agnieszka , Ciesielski Mariusz
Published: December 2024

Currently, people are more and more willing to rest in areas of urban greenery or forest areas for relaxation, sports, tourism, or recreation. Nonetheless, the decision for this type of activity is often a thoughtful, planned decision that determines the level of quality of life. The purpose of our study was to determine whether objective indicators of quality of life, such as social, economic, infrastructural, and environmental factors, influence the frequency of visits to urban green areas and forest areas. An online survey was conducted by a professional firm on a group of 1000 people living in and around the Warsaw metropolitan area. The results showed a clear seasonal pattern, with a higher frequency of visits in summer compared to winter. Urban green areas were more likely to be visited than forests. The frequency of visits was influenced by the 11 analysed factors, although not always in all variants. Among these factors were education level, income, distance to urban green areas, and assessment of the quality of greenery at the place of residence. Women and younger age groups were more frequent visitors, especially in summer, while older people and lower-income groups visited less often, especially in winter. The results underscore the importance of integrating green spaces with urban planning to increase accessibility and meet the diverse needs of the population, promoting both physical and mental well-being. Further research should be extended to other metropolitan areas and exploring psychological motivations for visiting natural areas.
Changes in Ginkgo biloba L.’s Habitat Due to Climate Change in China
Authors: Li Shenglin , Liu Xiaohuang , Shi Peng , Liu Jiufen , Zhu Ping , Liu Run , Xing Liyuan , Luo Xinping , Zhao Honghui , Zheng Yan , Bao Ruyi
Published: December 2024

Ginkgo biloba L. was named by Carl Linnaeus in 1771; a “living fossil” with immense medicinal and conservation value, it is a nationally first-class protected wild plant. However, many Ginkgo populations are under threat from habitat destruction, human exploitation, and over-harvesting, which have limited their numbers and range. Using an optimized MaxEnt model in R, this study analyzed Ginkgo distribution points and 22 ecological factors in China to explore the key environmental factors affecting its geographical distribution. The study also predicted the spatial distribution patterns and centroid changes of potential suitable areas under three different carbon emission pathways: current conditions, 2021–2040 (2030s), 2041–2060 (2050s), and 2061–2080 (2070s). The findings are as follows: (1) The optimal combination of model parameters (RM = 3.2, FC = LPH) reduced model complexity and overfitting and achieved very high prediction accuracy with an optimized AUC value of 0.928. (2) The key environmental factors influencing Ginkgo growth include precipitation in the driest month (20–175 mm), minimum temperature in the coldest month (−4 to 3 °C), precipitation in the hottest quarter (450–2500 mm), and a temperature seasonal variation deviation greater than 580. (3) Under the three future climate scenarios (SSP126, SSP245, and SSP585), the potential suitable habitat area for Ginkgo in China was increased, with the distribution range migrating to higher latitudes, Under the three different development models, the total suitable area followed this order: SSP126 > SSP245 > SSP585. Highly and moderately suitable areas are concentrated in the Yangtze River Basin. This study is highly significant for the ecological protection of Ginkgo, aiding in the rational planning of potential suitable areas, enhancing the monitoring of key conservation areas, and developing effective protection strategies in a timely manner.
Biofilm-Based Immobilization Fermentation for Continuous hEGF Production in Saccharomyces cerevisiae
Authors: Zhi Kaiqi , An Zhiguo , Zhang Mingyang , Liu Kehan , Cai Yafan , Wang Zhenyu , Zhang Di , Liu Jinle , Wang Zhi , Zhu Chenjie , Liu Dong , Yang Sheng , Ying Hanjie
Published: December 2024

Biofilms can enhance industrial fermentation efficiency by increasing cell density, stability, and metabolic activity and have been successfully applied to the continuous production of many small-molecule chemicals. However, the continuous production of proteins by biofilms has been less studied. This study used secretory human epidermal growth factor (hEGF) as a representative product to evaluate and optimize biofilm-based continuous protein production. First, by deleting the protease and overexpressing eight key genes involved in protein secretion in Saccharomyces cerevisiae, the yield of hEGF was improved by 82.6% from 77.4 to 141.3 mg/L in shake flasks. Subsequently, the flocculation genes FLO11 and ALS3 were introduced to facilitate the establishment of a biofilm-based continuous immobilization fermentation model. The optimal strain SIC-ALS3-PDI1 produced 583.8 mg/L of hEGF, with a productivity of 4.9 mg/L/h during traditional free-cell fermentation, while it produced an average of 300.0 mg/L of hEGF in 10 continuous batches of biofilm-based fermentation, with a productivity of 6.3 mg/L/h. Although the hEGF production in biofilms was lower than that in free-cell fermentation, biofilm fermentation demonstrated greater productivity, with the advantage of not requiring seed culture for each batch of fermentation. This study provided a valuable reference for the biofilm-based production of other peptides.
A Comparative Study of the User Interaction Behavior and Experience in a Home-Oriented Multi-User Interface (MUI) During Family Collaborative Cooking
Authors: Zhou Mengcai , Li Minglun , Ono Kenta , Watanabe Makoto
Published: December 2024

This study sought to ascertain the necessity of crafting specialized multi-user interfaces for scenarios involving multiple users and to provide guidance for the design of multi-user human–computer interactions by identifying the disparities in the interaction behavior and user experience when employing a conventional one-user interface (OUI) recipe versus a multi-user interface (MUI) recipe in the context of family collaborative cooking. To address this objective, this study employed a before-and-after comparison approach. Subsequently, adult users submitted self-assessments of their experiences using the OUI and MUI. The evaluation tools included a user experience survey questionnaire and a Likert seven-point scale, including aspects such as visual confirmation, content, operation, and satisfaction. Post-experiment interviews were also conducted with family members. The MUI exhibited greater effectiveness in terms of visual confirmation, with the “layout” assuming a role analogous to that of “text” in facilitating visual confirmation. Moreover, the operation of the MUI was found to be somewhat enjoyable. Nevertheless, no significant disparities were observed between the OUI group and the MUI group concerning content readability and most operational aspects. Furthermore, the users described their satisfaction with the MUI to be superior to that of the OUI, offering fun, convenience, and a clear appearance. Findings from my research clearly demonstrate that it is both valuable and essential to design a dedicated MUI.
Transmitted Light Measurement to Determine the Local Structural Characteristics of Paperboard: Grammage, Thickness, and Fiber Orientation
Authors: Sanjon Cedric W. , Leng Yuchen , Hauptmann Marek , Groche Peter , Majschak Jens-Peter
Published: December 2024

This study presents a novel transmission-based method for characterizing local structural features, including the grammage, thickness, and fiber orientation, of paper materials. Some non-destructive techniques, such as micro-computed tomography (μ-CT), microscopy, and radiation-based methods, are costly, time-consuming, and lack the ability to provide comprehensive local structural information within a single measurement. The proposed method utilizes a single light transmission measurement to assess local grammage and thickness through histogram matching with reference data obtained via β-radiography and profilometry. The same light transmission images are also used to determine local fiber orientation, employing image analysis techniques. The structure tensor method, which analyzes gradients of light transmission images, provides detailed insight into the local fiber orientation. The results show that thickness and grammage measurements are independent of which side of the paper is evaluated, while the fiber orientation distribution varies between the front and back sides, reflecting differences in fiber arrangement due to manufacturing processes. Various distribution functions are compared, and the Pearson Type 3, log-normal, and gamma distributions are found to most accurately describe the grammage, thickness, and fiber orientation distributions. The study includes a variety of paper types, ensuring a robust and comprehensive analysis of material behavior, and confirms that the method can effectively infer the inhomogeneous features from a single light transmission measurement.
Experimental Study of the Influence of an Asymmetric Tunnel Structure on the Maximum Ceiling Temperature in a V-Shaped Tunnel Fire
Authors: Dong Qiwei , Li Junmei , Li Yanfeng , Lu Huimin , Zhao Hengxuan
Published: December 2024

The smoke diffusion characteristics in an asymmetric V-shaped tunnel located at the slope change point were studied by experiments in a 1/20 small-scale tunnel. The influences of the slope composition of the V-shaped tunnel and fire heat release rate (fire HRR) on the fire-induced airflow velocity in the tunnel and maximum ceiling temperature rise were the focuses. The results show that due to the height difference between the two ports of the asymmetric tunnel, the resulting thermal pressure difference between the two sides of the tunnel drives the smoke to flow toward the large slope side and the inlet-induced airflow velocity increases with the increases in the slope difference and the HRR. The dimensionless inlet-induced airflow velocity v* is proportional to φ10.525H*0.634φ1−0.223Q*0.288. The maximum ceiling temperature rise increases with the increase in the HRR and decreases with the slope differences between the two side tunnels. An empirical model of the dimensionless induced airflow speed and the maximum temperature rise was proposed.
Numerical Simulation Analysis of an Offshore Multi-Row Arrangement Longline Aquaculture Facility with Lantern Nets Under Environmental Loads
Authors: Mu Yingna , Liang Guoxuan , Chen Changping , Zhang Ruitong , Teng Fei , Tan Yanbin
Published: December 2024

The structural hydrodynamic response of longline aquaculture facilities under the influence of waves and currents is complex. Studying the hydrodynamic characteristics of this aquaculture structure in complex sea environments can contribute to sustainable offshore aquaculture solutions. Thus, we established a numerical model using AquaSim2.18, a proven and effective finite element hydrodynamic software for analyzing the maximum tension in mooring lines and main lines, the displacement of the main lines, and the forces on the lantern nets under waves and currents. The results showed that positioning the system in the direction of incidence of waves and currents minimizes tension in both mooring and main lines, making a downstream arrangement optimal; compared with a single row, the maximum reduction in the tension of the mooring lines is 3.3% and 1.8% for five-row and row-row lines, respectively, and the shadow effects reduced the downstream mooring force. Additionally, line tension increased with wave height and current velocity, whereas wave periods had variable effects due to the period range; the lantern net forces increased with wave height and decreased with wave period. Wave height was also shown to influence the horizontal displacement of main lines. The findings can provide a reference for the hydrodynamic characteristics of different components of the structure.
Assessment of Immobilized Lacticaseibacillus rhamnosus OLXAL-1 Cells on Oat Flakes for Functional Regulation of the Intestinal Microbiome in a Type-1 Diabetic Animal Model
Authors: Nelios Grigorios , Prapa Ioanna , Mitropoulou Gregoria , Kompoura Vasiliki , Balafas Evangelos , Kostomitsopoulos Nikolaos , Yanni Amalia E. , Kourkoutas Yiannis
Published: December 2024

The aim of this study was to examine the effect of free or immobilized Lacticaseibacillus rhamnosus OLXAL-1 cells on oat flakes on the gut microbiota and metabolic and inflammatory markers in a streptozotocin (STZ)-induced Type-1 Diabetes Mellitus (T1DM) animal model. Forty-eight male Wistar rats were assigned into eight groups (n = 6): healthy or diabetic animals that received either a control diet (CD and DCD), an oat-supplemented diet (OD and DOD), a diet supplemented with free L. rhamnosus OLXAL-1 cells (CFC and DFC), or a diet supplemented with immobilized L. rhamnosus OLXAL-1 cells on oat flakes (CIC and DIC). Neither L. rhamnosus OLXAL-1 nor oat supplementation led to any significant positive effects on body weight, insulin levels, plasma glucose concentrations, or lipid profile parameters. L. rhamnosus OLXAL-1 administration resulted in a rise in the relative abundances of Lactobacillus and Bifidobacterium, as well as increased levels of lactic, acetic, and butyric acids in the feces of the diabetic animals. Additionally, supplementation with oat flakes significantly reduced the microbial populations of E. coli, Enterobacteriaceae, coliforms, staphylococci, and enterococci and lowered IL-1β levels in the blood plasma of diabetic animals. These findings suggested that probiotic food-based strategies could have a potential therapeutic role in managing dysbiosis and inflammation associated with T1DM.
The Effects of Ultrasound on the Rehydration of Konjac Glucomannan/Soy Protein Isolate Gel and Simulation of Gas-Liquid Interface Evolution During the Rehydration Process
Authors: Yan Jiqiang , Jiang Shizhong , Wang Qin , Dai OuJun , Yang Zhuoer , Huang Biyao , Huang Ruoyu , Chi Zhenghao , Sun Yilan , Pang Jie
Published: December 2024

Soy protein isolate (SPI) possesses potential gelling properties, making it suitable for gel-based applications. However, the gel network stability and mechanical properties of SPI are relatively poor and can be improved through modifications or by combining it with other polymers, such as Konjac Glucomannan (KGM). Combining SPI with KGM can overcome the poor gel network stability and mechanical properties of SPI, but it reduces the water-absorbing capacity of the gel network after drying, which affects the quality characteristics of plant-based protein rehydrated foods and limits the economic feasibility of soy protein foods. In this study, SPI and KGM are the main research objects. By using the alkali method to construct SPI/KGM dry gels with good gel properties, the influence of different ultrasonic powers on the rehydration kinetics and performance changes of SPI/KGM dry gels is examined. The speed and state of water entering the pores are simulated by constructing different pore-size capillary filling models, and the rehydration mechanism of the gel is elucidated. This study provides research ideas and a theoretical basis for the application of ultrasonic wave technology in the study of dry product rehydration performance.
Research Progress in the Extraction, Structural Characteristics, Bioactivity, and Commercial Applications of Oat β-Glucan: A Review
Authors: Li Xiaolu , Wu Yicheng , Duan Ruilin , Yu Haoran , Liu Siyao , Bao Yulong
Published: December 2024

Oats (Avena sativa L.) are an important cereal crop with diverse applications in both food and forage. Oat β-glucan has gained attention for its beneficial biological activities, such as reducing cardiovascular risk, preventing diabetes, and enhancing intestinal health. Despite its potential, more comprehensive research is required to explore its preparation, modification, bioactivities, and applications. This review highlights recent advancements in the determination and preparation of oat β-glucan, explores its biological activities and mechanisms, and examines the impact of food processing techniques on its properties. This review is intended to provide a theoretical foundation and reference for the development and application of oat β-glucan in the functional food industry.
Preparation of Antioxidant Peptides from Chicken Bone Proteins and the Influence of Their Compositional Characteristics on Antioxidant Activity
Authors: Jin Yitong , Zhou Peng , Zhu Chengzhi , Liu Yanan , Zhao Zhijun
Published: December 2024

Antioxidants play an important role in maintaining health and enhancing food stability by neutralizing free radicals. This study aimed to extract antioxidant peptides from white-feathered chicken bones through enzymatic hydrolysis, optimize the enzymatic hydrolysis conditions, and further investigate the relevance between the amino acid composition, molecular weight, and antioxidant activity of the resulting chicken bone hydrolysate. Alcalase was the most effective enzyme for hydrolyzing cooked chicken bones compared with papain, pepsin, and trypsin, yielding hydrolysates with the highest DH and ABTS radical scavenging activity. The enzymatic conditions were optimized using single-factor experiments and response surface methodology (RSM). The optimal conditions were a substrate concentration of 10%, an enzyme-substrate ratio of 502.75 U/g, a hydrolysis temperature of 48.48 °C, and a hydrolysis time of 1.13 h. Under these conditions, the ABTS radical scavenging activity reached 83.43%. Amino acid composition analysis revealed that peptides from chicken bones were rich in glycine, glutamic acid, alanine, proline, and aspartic acid, which were associated with antioxidant functions. Among these peptides, those with a molecular weight below 3 kDa exhibited the highest antioxidant effects through membrane filtration. In summary, chicken bone hydrolysate exhibits potent antioxidant activity, nominating them for potential application as natural antioxidants investible in novel functional foods and pharmaceuticals.