bluuebunny/crossref_metadata_2025 huggingface dataset:
Ethical Issues in Uncontrolled Donation After Circulatory Determination of Death: A Scoping Review to Reveal Areas of Broad Consensus, and Those for Future Research
Authors: Georgiou Anastasia , Tan Weiyi , Ionescu Mihnea I. , Kuhn Isla L. , Fritz Zoe
Published: February 2025

Uncontrolled donation after circulatory determination of death (uDCD) protocols are established in several countries with good outcomes. We reviewed the literature between 1997 and 2024 to identify ethical issues. 33 papers were identified. Several areas of continued ethical debate were delineated: the role of advanced life support techniques; the ethical acceptability of aortic occlusion balloons; the nature and timing of consent to organ preserving techniques; whether best interests can/should extend beyond individual bodily integrity in this context. Further empirical research and ethical analyses are needed in these domains. Broad consensus was identified on several issues including: decisions about termination of resuscitation and entry into a uDCD protocol should be made by different teams; at least 20–30 min of cardio-pulmonary resuscitation is required; a hands-off period of 5–7 min is required alongside continuous monitoring; organ preserving techniques should be as minimally invasive as possible; families should be approached early to discuss organ donation by trained staff; public knowledge and engagement about uDCD is poor and must be improved; transparency and informed consent are essential for potential uDCD organ recipients. To maintain transparency and encourage positive public engagement we propose a name change from uDCD to Organ Donation after Sudden Irreversible Cardiac Arrest (ODASICA).
Nonparametric Probability Density Function Estimation Using the Padé Approximation
Authors: Aghamiri Hamid Reza , Hosseini S. Abolfazl , Green James R. , Oommen B. John
Published: February 2025

Estimating the Probability Density Function (PDF) of observed data is crucial as a problem in its own right, and also for diverse engineering applications. This paper utilizes two powerful mathematical tools, the concept of moments and the relatively little-known Padé approximation to achieve this. On the one hand, moments encapsulate crucial information that is central to both the “time-” and “frequency-”domain representations of the data. On the other hand, the Padé approximation provides an effective means of obtaining a convergent series from the data. In this paper, we invoke these established tools to estimate the PDF. As far as we know, the theoretical results that we have proven, and the experimental results that confirm them, are novel and rather pioneering. The method we propose is nonparametric. It leverages the concept of using the moments of the sample data—drawn from the unknown PDF that we aim to estimate—to reconstruct the original PDF. This is achieved through the application of the Padé approximation. Apart from the theoretical analysis, we have also experimentally evaluated the validity and efficiency of our scheme. The Padé approximation is asymmetric. The most unique facet of our work is that we have utilized this asymmetry to our advantage by working with two mirrored versions of the data to obtain two different versions of the PDF. We have then effectively “superimposed” them to yield the final composite PDF. We are not aware of any other research that utilizes such a composite strategy, in any signal processing domain. To evaluate the performance of the proposed method, we have employed synthetic samples obtained from various well-known distributions, including mixture densities. The accuracy of the proposed method has also been compared with that gleaned by several State-Of-The-Art (SOTA) approaches. The results that we have obtained underscore the robustness and effectiveness of our method, particularly in scenarios where the sample sizes are considerably reduced. Thus, this research confirms how the SOTA of estimating nonparametric PDFs can be enhanced by the Padé approximation, offering notable advantages over existing methods in terms of accuracy when faced with limited data.
Experimental and Numerical Assessment of Crashworthiness Properties of Composite Materials: A Review
Authors: Falaschetti Maria Pia , Semprucci Francesco , Birnie Hernández Johan , Troiani Enrico
Published: February 2025

Crashworthiness is a critical property that enables aerospace structures to minimise injuries and equipment damage during impact scenarios. This review examines the current state of crashworthiness research, with a focus on regulatory frameworks, experimental testing, and numerical modelling techniques. Stringent safety standards set by the Federal Aviation Administration (FAA) and the European Union Aviation Safety Agency (EASA) guide the design and certification protocols for aeronautical structures. Experimental crash testing, which includes both full-scale and subscale impact tests, provides essential data for validating material behaviour and energy absorption capabilities under both quasi-static and dynamic loading conditions. Advanced numerical modelling tools offer significant insights into crash behaviour, enabling optimisation of structural designs whilst reducing reliance on costly physical testing. This review highlights the integration of regulations, empirical data, and computational tools in advancing crashworthiness research, with an emphasis on developing safer, more efficient, and sustainable aerospace designs. Future directions should prioritise the use of sustainable materials and optimise crashworthy designs through artificial intelligence (AI) and advanced numerical models to enhance structural performance and safety.
Simulating Soil Moisture Dynamics in a Diversified Cropping System Under Heterogeneous Soil Conditions
Authors: Engels Anna Maria , Gaiser Thomas , Ewert Frank , Grahmann Kathrin , Hernández-Ochoa Ixchel
Published: February 2025

Agro-ecosystem models are useful tools to assess crop diversification strategies or management adaptations to within-field heterogeneities, but require proper simulation of soil water dynamics, which are crucial for crop growth. To simulate these, the model requires soil hydraulic parameter inputs which are often derived using pedotransfer functions (PTFs). Various PTFs are available and show varying performance; therefore, in this study, we calibrated and validated an agro-ecosystem model using the Hypres PTF and the German Manual of Soil Mapping approach and adjusting bulk density for the top- and subsoil. Experimental data were collected at the “patchCROP” landscape laboratory in Brandenburg, Germany. The daily volumetric soil water content (SWC) at 12 locations and above ground biomass at flowering were used to evaluate model performance. The findings highlight the importance of calibrating agro-ecosystem models for spatially heterogeneous soil conditions not only for crop growth parameters, but also for soil water-related processes—in this case by PTF choice—in order to capture the interplay of top- and especially subsoil heterogeneity, climate, crop management, soil moisture dynamics and crop growth and their variability within a field. The results showed that while the impact of bulk density was rather small, the PTF choice led to differences in simulating SWC and biomass. Employing the Hypres PTF, the model was able to simulate the climate and seasonal crop growth interactions at contrasting soil conditions for soil moisture and biomass reasonably well. The model error in SWC was largest after intense rainfall events for locations with a loamy subsoil texture. The validated model has the potential to be used to study the impact of management practices on soil moisture dynamics under heterogeneous soil and crop conditions.
Humic Substances: Bridging Ecology and Agriculture for a Greener Future
Authors: Maffia Angela , Oliva Mariateresa , Marra Federica , Mallamaci Carmelo , Nardi Serenella , Muscolo Adele
Published: February 2025

Humic substances (HSs) are emerging as multifunctional natural catalysts in sustainable agriculture, offering novel opportunities to enhance soil health, plant productivity, and environmental resilience. This review synthesizes recent insights into the chemical diversity, biological mechanisms, and ecological impacts of HSs, presenting a new perspective on their role as dynamic agents in agroecosystems. Derived from decomposed organic matter, HSs regulate critical processes such as nutrient cycling, carbon sequestration, and pollutant detoxification. Unlike plant and microbial biomass, which undergo rapid mineralization due to their active dynamism, HSs exhibit significant resistance to biodegradation, leading to a prolonged residence time in soil that spans years or even centuries. This stability allows HSs to maintain their functional roles over extended periods, contributing to long-term soil health and ecosystem sustainability. Their integration into agricultural systems has demonstrated profound effects, including improved soil structure, increased water retention, and the stimulation of microbial activity, which collectively bolster plant stress tolerance and yield. Notably, it has been proposed that HSs exhibit hormone-like properties, influencing plant signaling pathways to enhance root architecture and nutrient acquisition. Moreover, HSs contribute to environmental remediation by regulating the leaching of heavy metals, mitigating nutrient runoff, and fostering climate resilience. This review highlights the synergistic potential of combining HSs with organic amendments like compost and biochar, positioning HSs as a cornerstone of regenerative farming practices. Addressing challenges such as variability in composition and application methods, the discussion underscores the urgency of developing standardized approaches to harness their full potential. By framing HSs as versatile and adaptive tools, this review paves the way for advancing sustainable agricultural systems while addressing global challenges like food security and climate change.
AdaptiveSwin-CNN: Adaptive Swin-CNN Framework with Self-Attention Fusion for Robust Multi-Class Retinal Disease Diagnosis
Authors: Qureshi Imran
Published: February 2025

Retinal diseases account for a large fraction of global blinding disorders, requiring sophisticated diagnostic tools for early management. In this study, the author proposes a hybrid deep learning framework in the form of AdaptiveSwin-CNN that combines Swin Transformers and Convolutional Neural Networks (CNNs) for the classification of multi-class retinal diseases. In contrast to traditional architectures, AdaptiveSwin-CNN utilizes a brand-new Self-Attention Fusion Module (SAFM) to effectively combine multi-scale spatial and contextual options to alleviate class imbalance and give attention to refined retina lesions. Utilizing the adaptive baseline augmentation and dataset-driven preprocessing of input images, the AdaptiveSwin-CNN model resolves the problem of the variability of fundus images in the dataset. AdaptiveSwin-CNN achieved a mean accuracy of 98.89%, sensitivity of 95.2%, specificity of 96.7%, and F1-score of 97.2% on RFMiD and ODIR benchmarks, outperforming other solutions. An additional lightweight ensemble XGBoost classifier to reduce overfitting and increase interpretability also increased diagnostic accuracy. The results highlight AdaptiveSwin-CNN as a robust and computationally efficient decision-support system.
Effects of Increased Housing Space Without Altering Stocking Density on Body Weight, Stress, and Gut Microbiome in Broiler Chickens
Authors: Kim Eun Bae , Choi Seojin , Park Jongbin , Xuan Biao
Published: February 2025

Effective poultry management practices that promote chicken health are crucial for producing higher-quality chicken meat at a lower cost. This study examined the hypothesis that increasing space while maintaining stocking density may positively impact poultry health. We evaluated body weight (BW) as an indicator of growth, stress markers, and the composition of the gut microbiome by comparing two housing sizes: smaller (control) and larger (treatment) spaces, with 10 birds per space and a stocking density of 12.3 birds/m2. Chickens in the larger space had 15% higher BW (p = 0.06) compared to those in the smaller space when significance was evaluated at p < 0.10. Stress indicators such as blood cortisol (acute) and brain FKBP51 did not differ significantly. Faith’s phylogenetic diversity was marginally higher in the larger space (p = 0.05), and microbial communities differed significantly between the two groups. The relative abundance of several genera, including Clostridium_sensu_stricto_1 (p = 0.02), Lactobacillus (p = 0.03), and Paracoccus (p < 0.01), was greater in the larger space, whereas Turicibacter (p = 0.02), Escherichia–Shigella (p = 0.01), and Lysinibacillus (p = 0.01) were more abundant in the smaller space. The larger and smaller spaces were associated with a significant (p < 0.05) increase in the abundance of 39 and 25 MetaCyc pathways, respectively, involved in amino acid and nitrogen metabolisms. These findings suggest that increasing housing space without altering stocking density or additional treatments may improve both growth and gut microbiome health in broilers. Our results provide insights into the relationship between chicken housing environments and the gut microbiome.
Recent Issues in the Development and Application of Targeted Therapies with Respect to Individual Animal Variability
Authors: Kurhaluk Natalia , Tkaczenko Halina
Published: February 2025

This literature review explores the impact of molecular, genetic, and environmental factors on the efficacy of targeted therapies in veterinary medicine. Relevant studies were identified through systematic searches of PubMed, Web of Science, Scopus, and ScienceDirect using keywords such as “species-specific treatment strategies”, “signalling pathways”, “epigenetic and paragenetic influences”, “targeted therapies”, “veterinary medicine”, “genetic variation”, and “free radicals and oxidative stress”. Inclusion criteria included studies focusing on species-specific therapeutic responses, genetic influences, and oxidative stress. To ensure that only the most recent and relevant evidence was included, only peer-reviewed publications from the last two decades were considered. Each study selected for analysis was critically appraised, with a particular emphasis on methodological quality, experimental design, and scientific contribution to the understanding of how environmental and biological factors influence therapeutic outcomes. A special emphasis was placed on studies that used a comparative, cross-species approach to assess variability in therapeutic responses and potential adverse effects. The review synthesises evidence on the role of epigenetic and paragenetic factors and highlights the importance of cross-species studies to understand how environmental and biological factors influence treatment outcomes. By highlighting genetic variation, oxidative stress, and individual species differences, the review argues for personalised and species-specific therapeutic approaches. The review emphasises that such an approach would improve veterinary care and inform future research aimed at optimising targeted therapies, ultimately leading to better animal health and treatment efficacy. A key contribution of the review is its emphasis on the need for more personalised treatment protocols that take into account individual genetic profiles and environmental factors; it also calls for a greater integration of cross-species studies.
Risk Assessment of Global Animal Melioidosis Under Current and Future Climate Scenarios
Authors: Li Suya , Xu Le , Jiao Yuqing , Li Shiyuan , Yang Yingxue , Lan Feng , Chen Si , Man Churiga , Du Li , Chen Qiaoling , Wang Fengyang , Gao Hongyan
Published: February 2025

Melioidosis is a zoonotic disease that is caused by Burkholderia pseudomallei, which is a serious public health and safety risk. In order to explore the global animal melioidosis risk distribution and its dynamic response to future climate scenarios, we collected global data about reported animal incidence sites. Data regarding the density of Burkholderia pseudomallei in the environment were created by collecting and sorting information about the Burkholderia pseudomallei occurrence sites in contaminated air, soil, and water. Combined with bioclimatic variables, the maximum entropy (MaxEnt) niche was modeled for global animal melioidosis. The findings indicate that under current bioclimatic conditions, global animal melioidosis risk regions are concentrated between 30° S and 30° N, with high-risk areas being mainly in Central America, the northern part of South America, and eastern and southern India, among others. Most countries will expand their risk regions under future climatic scenarios. Melioidosis risk expanding towards higher northern latitudes has led to new epidemic areas. In addition, the melioidosis risk area will contract in some areas. Therefore, we have provided a basis for global melioidosis surveillance and propose feasible strategies for prevention and control in high-risk regions, which will help countries to carry out targeted surveillance and prevention to reduce risks and losses.
Dietary Effects of Different Proportions of Fermented Straw as a Corn Replacement on the Growth Performance and Intestinal Health of Finishing Pigs
Authors: Ji Xiaoguang , Tong Wenfei , Sun Xiangxue , Xiao Lei , Wu Mengjun , Li Peng , Hu Yonggang , Liang Yunxiang
Published: February 2025

The aim of the present study was to investigate the dietary effects of replacing corn with different proportions of fermented straw on the growth performance and intestinal health of finishing pigs. A total of 275 healthy commercial finishing pigs aged 126 days (average body weight, 82.96 ± 3.07 kg) were randomly allocated into three groups: the control (CTR, basal diet) group, the 5% fermented straw (FJJG5, replacing 5% of the corn) group, and the 10% fermented straw (FJJG10, replacing 10% of the corn) group. There were six replicates in each group and 14–16 pigs per replicate. On day 39 of the experiment, one animal from each replicate was slaughtered for sampling and for further analysis. The results showed that the finishing pigs in the FJJG10 group had a reduced average daily weight gain and an increased feed-to-gain ratio. The FJJG5 group had reduced total cholesterol, high-density lipoprotein, and low-density lipoprotein in their serum, while the FJJG5 and FJJG10 groups had reduced contents of lactate dehydrogenase. In addition, the FJJG5 group exhibited increased T-SOD activity and MDA content in the colon, while the FJJG10 group also showed increased T-AOC activity in their serum and increased contents of MDA in the colon. The FJJG5 group exhibited increased activities of jejunal disaccharidase and lipase, while the FJJG10 group exhibited decreased jejunal crypt depths. Moreover, the FJJG5 group presented an increased relative expression of APOA4, LPL, and MUC2 but decreased SLC7A7 and IL-10 in the jejunum and APOA4 in the colon. The FJJG10 group exhibited a decreased relative expression of SLC7A7 and IL-10 in the jejunum and decreased MMP13, KCNJ13, APOA4, SLC7A7, LPL, and IL-10 in the colon. Furthermore, the FJJG5 group exhibited an increased relative abundance of Lactobacillus in colon contents, while the FJJG10 group had a reduced relative abundance of streptococcus. In conclusion, 5% fermented straw can improve the lipid metabolism and colon microbiota structure of finishing pigs, while 10% fermented straw has adverse effects on the growth performance and intestinal health of finishing pigs.
An Adaptive Gradient Algorithm for Solving the Buffer Allocation Problem in Unreliable Production Lines
Authors: Li Lei , Chen Mengqiao
Published: February 2025

The optimal allocation of buffers is an important research issue in the area of manufacturing system design and optimization, as buffers can have a large impact on system performance. In this study, we consider one of the most common buffer allocation problems in unreliable production lines: maximizing the throughput of a line subject to a total buffer capacity constraint. We propose an efficient gradient algorithm to solve this problem. Compared to the existing gradient algorithms based on approximate evaluation methods, the proposed algorithm uses simulation to evaluate throughput and can be applied to a wider range of systems, such as production lines with non-exponential failures. To address the challenge posed by the time-consuming nature of simulation, the algorithm employs an adaptive search mechanism that can greatly reduce the number of simulation runs. The algorithm automatically sets the initial search step size based on the scale of buffer allocation problems and dynamically adjusts it during the search process. The algorithmic complexity is characterized as O(lnN), where N denotes the total buffer capacity to be allocated. Numerical results demonstrate that the adaptive gradient algorithm is as accurate as the fixed-step gradient algorithm, while the computational time required is significantly reduced. Therefore, the algorithm shows a substantial advantage in solving large-scale buffer allocation problems.
Development of Enhanced Stress Prediction Models for Fixed Traffic Loads on Flexible Pavements Based on Response Surface Methodology (RSM) and Machine Learning (ML) Techniques
Authors: Alnadish Adham Mohammed , Bangalore Ramu Madhusudhan , Baarimah Abdullah O. , Alawag Aawag Mohsen
Published: February 2025

Pavement design is influenced by traffic load, which affects its lifespan. Traditional methods classify traffic load into fixed traffic, fixed vehicle, variable traffic, and vehicle/axle loads. In fixed traffic, pavement thickness is based on the maximum expected wheel load without considering load repetitions. Meanwhile, in fixed vehicle scenarios, it is calculated by the repetitions of a standard axle load. For nonstandard axle loads, the equivalent axle load is determined by multiplying repetitions by the corresponding equivalent load factor. In variable traffic, each axle and its repetitions are analyzed independently. This study proposes enhanced models for fixed traffic loads, focusing on single, dual, and tridem axles in a single-layer pavement model, to improve stress prediction accuracy. The results show that a quadratic model with a base-10 logarithmic transformation accurately predicts stresses. Additionally, machine learning models, especially Gradient Boosting, provided more accurate predictions than traditional models, with lower mean squared error (MSE) and root mean squared error (RMSE). The results show that these models are effective in predicting the stress in pavement. These findings provide valuable insights that can lead to better pavement design and more effective maintenance practices.
Automated Detection and Biomarker Identification Associated with the Structural and Functional Progression of Glaucoma on Longitudinal Color Fundus Images
Authors: Majid Iyad , Mishra Zubin , Wang Ziyuan Chris , Chopra Vikas , Heuer Dale , Hu Zhihong Jewel
Published: February 2025

The diagnosis of primary open-angle glaucoma (POAG) progression based on structural imaging such as color fundus photos (CFPs) is challenging due to the limited number of early biomarkers, as commonly determined by clinicians, and the inherent variability in optic nerve heads (ONHs) between individuals. Moreover, while visual function is the main concern for glaucoma patients, and the ability to infer future visual outcome from imaging will benefit patients by early intervention, there is currently no available tool for this. To detect glaucoma progression from ocular hypertension both structurally and functionally, and identify potential objective early biomarkers associated with progression, we developed and evaluated deep convolutional long short-term memory (CNN-LSTM) neural network models using longitudinal CFPs from the Ocular Hypertension Treatment Study (OHTS). Patients were categorized into four diagnostic groups for model input: healthy, POAG with optic disc changes, POAG with visual field (VF) changes, and POAG with both optic disc and VF changes. Gradient-weighted class activation mapping (Grad-CAM) was employed for the post hoc visualization of image features, which may be associated with the objective POAG biomarkers (rather than the biomarkers determined by clinicians). The CNN-LSTM models for the detection of POAG progression achieved promising performance results both for the structural and functional models, with an area under curve (AUC) performance of 0.894 for the disc-only group, 0.911 for the VF-only group, and 0.939 for the disc and VF group. The model demonstrated high precision (0.984) and F1-score (0.963) in the both-changes group (disc + VF). Our preliminary investigation for early POAG biomarkers with Grad-CAM feature visualization signified that retinal vasculature could serve as an early and objective biomarker for POAG progression, complementing the traditionally used optic disc features and improving clinical workflows.
Nanomaterials in Photocatalysis: An In-Depth Analysis of Their Role in Enhancing Indoor Air Quality
Authors: Greco Enrico , De Spirt Alessia , Miani Alessandro , Piscitelli Prisco , Trombin Rita , Barbieri Pierluigi , Marin Elia
Published: February 2025

Since people spend most of their time in indoor environments, they are continuously exposed to various contaminants that threaten human health. The air quality in these settings is therefore a crucial factor in maintaining health safety. In order to reduce the concentration of indoor air pollutants and improve air quality, photocatalytic oxidation has drawn the attention of researchers. This study aims to provide a comprehensive view of the nanomaterials used in the photocatalytic oxidation of the most common pollutants in indoor environments. The effects of various parameters like humidity, airflow, deposition time, and light intensity were also evaluated, as they can significantly influence photocatalytic reactions. The most common nanomaterials used in photocatalysis are TiO2-based and, in this study, they were classified and examined based on their morphology. TiO2 doping with metals and non-metals has demonstrated an enhancement of its adsorption properties and photocatalytic efficiency for the removal of several pollutants. The role of carbon-based nanomaterials in photocatalysis was also evaluated due to their adsorption capabilities towards various pollutants. In addition, other less common photocatalysts such as ZnO, MnO2, WO3, CeO2, and CdS also exhibited high photocatalytic activity for pollutant degradation. Applications of these photocatalysts in air purifiers, paints, and building materials e.g., concrete, glass, and wallpapers, lead to efficient reduction of pollutants in indoor settings.
Plastic Waste to Carbon Adsorbent: Activation with Sodium Carbonate and Functionalization with Citric Acid
Authors: Pereira Ledicia , Martín-Lara María Ángeles , Garcia-Garcia Guillermo , Calvo Concepción , Robledo Tatiana , Solís Rafael R. , Calero Mónica
Published: February 2025

Plastic waste management is currently a challenge of great importance. The valorization of non-recyclable fractions into carbonaceous adsorbents is an interesting strategy that promotes the circular economy. In this work, a waste-to-adsorbent strategy was pursued with the char from plastic pyrolysis. The char (non-porous, surface area ~3 m2 g−1) was activated with chemical activation, with sodium carbonate boosting the textural properties (surface area ~418 m2 g−1, pore volume 0.436 cm3 g−1), triggering the formation of activated carbon with a large mesoporosity (71%). X-ray photoelectron spectroscopy and thermal programmed desorption characterization confirmed the enrichment of the surface with carboxylic groups by treatment with citric acid, with a slight loss of textural properties. The activated carbon showed an enhanced adsorption uptake of lead in water (~52 mg g−1 functionalized vs. ~37 mg g−1 non-functionalized) and limited influence on the adsorption of acetaminophen. The preparation costs and the consumption cost per unit of removed pollutants confirm the benefits of the activation and functionalization of the original carbonaceous precursor. However, the possible metal lixiviation from plastic additives and the environmental impact according to a life cycle assessment still make this kind of valorization strategy controversial.
Physical and Sensory Properties of Vegan Organic Microalgae Pasta with High Protein and/or Fiber Content
Authors: Baune Marie-Christin , Fanari Fabio , Lickert Thomas , Schilling Frank , Claret Anna , Guerrero Luis , Bindrich Ute , Heinz Volker , Terjung Nino
Published: February 2025

Market opportunities for microalgae pasta increase if an added health value can be declared. This work aimed to develop organic, vegan, protein- and/or fiber-rich microalgae pasta. Chlorella vulgaris (CV) at 3% and 5%, denatured wheat gluten (dG) and/or apple fibers (AF) were added to the dough and processing, cooking behavior, color, firmness, and sensory properties were investigated to test the influence of increasing protein and fiber contents and the impact of combined ingredients in comparison with the individual ingredients. For dG, the lowest impact on color and sensory changes (unaltered acceptance) was observed, but in combination with CV and AF, the overall effects were higher than with CV or AF alone. In addition, all dG-containing samples showed reduced water absorption and increased firmness, most likely due to a condensed protein network. CV and AF alone had no effect on firmness, but combinations did. AF slightly and 3% CV strongly affected odor, taste, and acceptance (27%) of the pasta. Combinations of CV with dG or AF increased the acceptability (45% and 36%, respectively), combinations of all ingredients worsened it (18%). We conclude that high protein and/or fiber Chlorella pasta is technically feasible, but that CV’s taste must be improved for greater acceptance.
Application of Ultrasonic Nondestructive Testing for Breeding of Meat Pigeons
Authors: Gao Ruiyuan , Hou Haobin , Zheng Suwei , Wang Xiaoliang , Ding Weixing , Tu Yingying , Li Xianyao , Yang Changsuo , Shen Xiaohui , Yao Junfeng
Published: February 2025

The aims of this study were to assess the correlation of breast muscle thickness (BMT) with the breast muscle weight (BMW), body weight (BW), breast width, and breast depth (BD) of meat pigeons, and to explore the feasibility of ultrasonic nondestructive testing (UNDT) for non-invasive measurements of BMT. It has been proven that using ultrasonic nondestructive testing specifically for evaluating the pectoral musculature yield in other poultry species such as Peking ducks and Yangzhou geese is feasible. The BMT of Carneau and Silver King pigeons (n = 103 each; age, 28 days) was measured at two points by UNDT. The correlation between the BMT at two points and BMW was analyzed. The results demonstrated that the correlation coefficients between BMT at point A and BMW were 0.907 and 0.897 in Carneau and Silver King pigeons, respectively, with significant regression relationships (p < 0.01). Variety and sex had little effect on BMT measurements. Six optimal univariate linear regression equations were established. The regression relationship was very significant, as determined by the F-test (p < 0.01), indicating an actual regression relationship between the variables of each equation and that UNDT can be applied for the breeding of meat pigeons. This represents the first application of ultrasonic nondestructive testing specifically for evaluating pectoral musculature yield in pigeons intended for meat production.
Experiment and Analytical Model for Pore Structure of Early-Age Composite Cement Pastes by LF-NMR
Authors: Wu Jincheng , Yang Guo , Hong Bin , Liu Xiaolin
Published: February 2025

This study investigated mineral admixtures that are often utilized as replacements for cement in high-performance concrete with a view to enhancing their durability and workability. The properties of concrete are closely related to the structure of its pores. This research employed low-field nuclear magnetic resonance technology to explore the influence of water-to-cement ratio, curing time, and mineral admixture content on the pore structure of early-age cement pastes. The findings indicated that the pore size distribution curves of all composite cement pastes display a distinct bimodal nature. The size of gel pores increases with a higher water-to-cement ratio, but decreases as the curing period extends. Fly ash, slag, and silica fume improve the pore structure at 14 days, 7 days, and 3 days, respectively. The addition of admixtures has little effect on the most probable pore diameter, but raises the proportion of gel pores with increasing content. In order to better fit the experimental data, a bimodal model integrating Shimomura and Maekawa’s model with the Weibull distribution function was introduced to describe the pore structure of cement pastes with or without fly ash, slag, and silica fume.
Honeybee Bioaccumulation as a Tool for Assessing the Environmental Quality of an Area Affected by the Activity of a Municipal Waste Sorting Facility (Central Italy)
Authors: Pallottini Matteo , Goretti Enzo , Gardi Tiziano , Petrarchini Marco , Pazzaglia Aron , Castellani Beatrice , Bruschi Federica , Petroselli Chiara , Selvaggi Roberta , Cappelletti David
Published: February 2025

The management of municipal solid waste presents a significant challenge for cities. Facilities dedicated to sorting, treating, and recycling waste (including plastic, glass, metals, aluminium, and wood) play a crucial environmental role in urban areas, contributing to sustainable development. Since combustion processes are not involved, any potential chemical impact of the facility on the surrounding area are likely to result from the emissions of metals and metalloids. In this study, the bioaccumulation of Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, V, and Zn in the tissues of honeybees (Apis mellifera ligustica) was employed as a reference to assess the environmental quality of the area near a municipal waste sorting and storage facility located in Ponte Rio, Perugia (Umbria, Central Italy), which serves as the case study here. No higher contamination levels were found in the facility area compared to the suburban territory of Perugia, where the bioaccumulation levels of these elements in honeybees frequently exhibited higher values. The application of the Honeybee Contamination Index (HCI) confirmed these results. Therefore, the operation of this waste sorting facility is sustainable concerning environmental contamination by chemicals.
Effects of Supplementation of Different Proteins on the Rheological Properties of Liquid Whole Eggs
Authors: Elayan Majd , Németh Csaba , Enkhbold Munkhnasan , Friedrich László , Dalmadi István , Varga-Tóth Adrienn
Published: February 2025

This study aimed to evaluate the impact of increasing total protein content on the rheological properties of liquid whole eggs. The study fills the gap between fundamental science and industrial application by exploring the potential for developing high-protein, functional egg products for health-conscious consumers and the food industry. Liquid whole egg samples were enriched with different percentages of egg white and whey proteins. Proteins were added either before or after heat treatment, followed by homogenization, to analyze the effects on rheological behavior. Results indicated that whey protein samples exhibit near-Newtonian behavior due to their high solubility and minimal protein interactions, while egg white protein samples, especially at higher concentrations, induce shear thinning behavior and increased viscosity due to their water-binding capacity and partial heat-induced denaturation. Flow behavior index (n) decreased by 62.7 ± 5.7% and 25.2 ± 1.8% for heat treated with 10% added egg white and whey protein samples, respectively; meanwhile, it decreased by 2.64 ± 0.06% for 10% of added egg white protein and increased by 12.0 ± 1.0% for 10% of whey protein when heat treatment was induced prior to protein additions. The findings from this study offer valuable insights for developing functional food enriched with whey and egg white proteins.
Application of Acoustic Emission Technique in Landslide Monitoring and Early Warning: A Review
Authors: Song Jialing , Leng Jiajin , Li Jian , Wei Hui , Li Shangru , Wang Feiyue
Published: February 2025

Landslides present a significant global hazard, resulting in substantial socioeconomic losses and casualties each year. Traditional monitoring approaches, such as geodetic, geotechnical, and geophysical methods, have limitations in providing early warning capabilities due to their inability to detect precursory subsurface deformations. In contrast, the acoustic emission (AE) technique emerges as a promising alternative, capable of capturing the elastic wave signals generated by stress-induced deformation and micro-damage within soil and rock masses during the early stages of slope instability. This paper provides a comprehensive review of the fundamental principles, instrumentation, and field applications of the AE method for landslide monitoring and early warning. Comparative analyses demonstrate that AE outperforms conventional techniques, with laboratory studies establishing clear linear relationships between cumulative AE event rates and slope displacement velocities. These relationships have enabled the classification of stability conditions into “essentially stable”, “marginally stable”, “unstable”, and “rapidly deforming” categories with high accuracy. Field implementations using embedded waveguides have successfully monitored active landslides, with AE event rates linearly correlating with real-time displacement measurements. Furthermore, the integration of AE with other techniques, such as synthetic aperture radar (SAR) and pore pressure monitoring, has enhanced the comprehensive characterization of subsurface failure mechanisms. Despite the challenges posed by high attenuation in geological materials, ongoing advancements in sensor technologies, data acquisition systems, and signal processing techniques are addressing these limitations, paving the way for the widespread adoption of AE-based early warning systems. This review highlights the significant potential of the AE technique in revolutionizing landslide monitoring and forecasting capabilities to mitigate the devastating impacts of these natural disasters.
Leveraging Large Language Models for Enhancing Safety in Maritime Operations
Authors: Miller Tymoteusz , Durlik Irmina , Kostecka Ewelina , Łobodzińska Adrianna , Łazuga Kinga , Kozlovska Polina
Published: February 2025

Maritime operations play a critical role in global trade but face persistent safety challenges due to human error, environmental factors, and operational complexities. This review explores the transformative potential of Large Language Models (LLMs) in enhancing maritime safety through improved communication, decision-making, and compliance. Specific applications include multilingual communication for international crews, automated reporting, interactive training, and real-time risk assessment. While LLMs offer innovative solutions, challenges such as data privacy, integration, and ethical considerations must be addressed. This review concludes with actionable recommendations and insights for leveraging LLMs to build safer and more resilient maritime systems.
Insights on the Influence of the Central-Cut Width of the Box Assembly with Removable Component on Its Dynamical Responses
Authors: Padilla Christopher , Flores Antonio , Madrid Jonah , Granillo Ezekiel , Abdelkefi Abdessattar
Published: February 2025

This investigation focuses on the dynamical effects caused by varying the central-cut width within the Box Assembly with Removable Component (BARC) system. The central-cut widths included in this study are a 0.5″ cut, a 0.25″ cut, a thin 0.1″ cut, and a structure that did not have a cut at all. Finite element analysis was conducted to determine the mode shapes and natural frequencies of each of the BARC structures. Structural dynamics experiments were run to examine the effects of the central-cut width on the dynamical responses and nonlinear characteristics of the BARC system. Free vibration testing with an impact hammer was carried out to excite the system and extract the dominant frequencies and directions of the significant responses. A pseudorandom vibration test that allows for the qualitative determination of any nonlinear behavior within the system was performed. This type of behavior can include nonlinear softening, nonlinear hardening, and the most common, nonlinear damping due to the presence of several bolted-joint connections and the possible activation of geometric and inertia nonlinearities. To quantitatively investigate the impacts of the central-cut width on the dynamics of the system, swept sinusoidal testing was conducted. It is determined that almost all systems with central cuts demonstrate the presence of nonlinear softening, but at times, nonlinear hardening trends are seen, particularly in the 0.1″ cut and no-cut systems when testing harmonically. Each of the central-cut systems displays nonlinear damping, with the amount of damping generally increasing as the central cut decreases in size. The effect of the central cut of the BARC system on the mode-switching ability of the system is negligible; however, mode switching takes place when comparing the central-cut configurations to the no-cut one. These results show the significance of accurately measuring the central-cut width and how geometric uncertainty may change the dynamical responses and nonlinear properties of the system.
Recent Spatiotemporal Changes of Subhourly Extreme Rainfall Events in Seoul
Authors: Shin Ju-Young , Park Jiyeon , Sung Kyungmin , Kim Yongseok
Published: February 2025

This study aims to examine the spatiotemporal variations of extreme rainfall events in Seoul, South Korea, utilizing subhourly rainfall data collected from an extensive observation network. Employing the Mann–Kendall trend detection test and Moran’s I index, this study analyzed temporal trends and spatial distributions in the extreme rainfall time series at 37 weather stations. The findings revealed that the annual maximum precipitation (AMP) series for various durations in Seoul generally exhibited a decreasing trend, with a marked decline observed for durations of 300 and 360 min. Furthermore, the study identified notable changes in the spatial patterns of AMP events, particularly for subhourly AMP events. The results indicate an intensification in the spatial concentration of AMP distribution. Consequently, despite the overall reduction in AMP, the likelihood of urban flooding may increase. This suggests that existing hydraulic design criteria, based on past concepts that temporal and spatial variability are constant, may no longer adequately represent extreme rainfall events. Therefore, revising these criteria to account for the evolving nature of extreme rainfall patterns is imperative.
Dragonfly-Inspired 3D Bionic Folding Grid Structure Design
Authors: Dong Xin , Yao Leijiang , Liu Hongjun , Ding You
Published: February 2025

The method proposed in this paper provides a new research idea for biomimetic three-dimensional grid structure material design. The wings of a dragonfly exhibit a complex grid structure, comprising approximately 1–2% of its total weight, yet demonstrating exceptional mechanical efficiency. In order to investigate the feasibility of applying the design optimization method simulating this structure to the material structure design, we adopted a multi-step method to realize the formation of multi-scale grid structures and folds. Initially, the main vein of the front wing was simulated using a branching structure generation technique. Subsequently, a Voronoi grid was overlaid to generate the complete bionic grid structure. Finally, the fold structure of the wing was simulated using origami principles to create a three-dimensional grid structure. This method can obtain the rigid–flexible coupling 3D grid structure by simulating the 3D fold structure design of the dragonfly wing. The results show that the proposed method can obtain structural materials with excellent structural properties by simulating the structural characteristics of dragonfly wings.
Coquaternion Transformations in Nonequilibrium Dynamics of Biologic Systems
Authors: Davydyan Garri
Published: February 2025

Imaginary coquaternions cℍ can be represented by matrices of negative feedback N−, positive feedback P+, and reciprocal links R±. An added environmental element E± endows biologic systems with the structure of cℍ module. Although cℍ representation links base patterns with the geometric structure of the pseudo-Euclidean R24 space, unknown physiologic aspects of relationships between base elements may add new functional features to the structure of a functional module. Another question is whether achieving and remaining in the equilibrium state provides stability for a biologic system. Considering the property of a biologic system to return deviated conditions to the equilibrium, the system of ordinary differential equations describing the behavior of a mechanical pendulum was modified and used as a basic tool to find the answers. The results obtained show that in evolving systems, the regulatory patterns are organized in a sequence NPRN of base elements, allowing the system to perform a high amount of energy-consuming functions. In order to keep dissipating energy at the same level, the system bifurcates and finalizes its regulatory cycle in R± by splitting P+ after which the next cycle may begin. Obtained flows are continuous pathways that do not interfere with equilibrium states, thus providing a homeostasis mechanism with nonequilibrium dynamics. Functional transformations reflect changes in the geometry and metric index of the coquaternion. Related coquaternion dynamics show the transformation of a hyperbolic hyperboloid into the closed surface, which is the fusion of the portions of the hyperbolic hyperboloid and two spheres.
The Creeping Gentrification of a Street: The Case of the Historic Oval-Shaped Kościelna Street in Poznań
Authors: Kapliński Oleg
Published: February 2025

The subject of the research is the attractive Kościelna Street connecting two prestigious districts of the city of Poznań (Jeżyce and Sołacz). The oval ring layout of the street with its characteristic green separation strip sets the tone for the entire district. The urban layout, preserved for almost 300 years, is tied to its pioneers—settlers brought from Bamberg (Upper Franconia, Bavaria). The problems of maintaining the historical identity of the place and its inhabitants as well as the identity of the architecture (transformation from farmstead to frontage layout) are highlighted. The phenomenon of gentrification is the background to the deliberations. A chronicle of events over three centuries allows it to be described as creeping. Nevertheless, three types of gentrification have been examined: economic, social and symbolic (cultural). Research methods in the context of the multidisciplinary nature of the issue, emerging dilemmas and an overview of street attractiveness research are discussed. A method based on the Net Promoter Score has been used as an aid to determine the attractiveness of an architectural structure. The importance of social and symbolic aspects has been pointed out so that gentrification does not become rapacious.