bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling and experimental analysis of protein matrix solidification in cooling dies during high-moisture extrusion
Authors: Högg Elisabeth , Horneber Tobias , Rauh Cornelia
Published: February 2025

Introduction

High-moisture extrusion (HME) has become a key method in the food industry for texturizing plant-based proteins to create high-moisture meat analogues (HMMAs) with meat-like textures. Despite its importance, the texturization process within the cooling die of the extruder remains not fully understood. This study aims to bridge this knowledge gap by combining experimental and numerical methods to analyze protein matrix solidification.

Methods

In-situ measurements, including temperature, pressure, velocity, and flow profiles, were conducted for various HME setups and die geometries. Numerical simulations based on the finite volume method incorporated thermophysical material properties from previous research to predict flow dynamics and structural changes. An inverse modeling approach was used to estimate unmeasurable parameters, and experimental validation included textural analysis, such as slice shear force and tensile strength.

Results

The experimental and numerical studies showed strong agreement, validating the numerical model’s accuracy in simulating cooling die processes. Flow profiles visualized experimentally and numerically highlighted the correlation between structuring coefficients derived from kinematic variables and textural analysis results. Key findings indicated that cooling die geometries and process conditions significantly influence protein matrix solidification and the resulting texture of HMMAs.

Discussion

This study provides novel insights into the dynamics within cooling dies and establishes a robust framework for optimizing HME processes to enhance the textural quality of meat analogues. The validated numerical model enables future studies to explore diverse geometries and process conditions, contributing to advancements in plant-based protein texturization.
The tumor coagulome as a potential biological determinant of postsurgical recurrence of oral squamous cell carcinoma
Authors: Saidak Zuzana , Galmiche Antoine
Published: February 2025

Objectives

The tumor coagulome is an intrinsic characteristic of human tumors and a key determinant of cancer-associated thrombosis (CAT). Oral Squamous Cell Carcinoma (OSCC) establish a local procoagulant state that contributes to a broad range of vascular complications, and potentially also to tumor progression. Recent clinical studies suggest that biomarkers of coagulation might be of interest for predicting postsurgical recurrence of OSCC, but it remains unclear whether specific properties of the coagulome of OSCC are conducive to postsurgical recurrence. We examined this possibility using transcriptomic analyses of OSCC.

Materials and methods

Using bulk RNA-seq data from TCGA and other sources, we explored the link between the coagulome (n = 85 genes) and disease-free survival (DFS) of OSCC with machine-learning. Tumor microenvironment analyses and single-cell RNA-seq analyses were used to address the potential mechanisms that link coagulation and tumor recurrence. We also compared the coagulome of matched primary/recurrent OSCC.

Results

We identified seven coagulation-related genes, either positively (F3, F2, F8 and PROC) or negatively (VWF, SERPING1, BDKRB2) linked to postsurgical recurrence in OSCC at low/intermediate risk, and we validated the model in an independent cohort. We examined their relationship with the tumor microenvironment, suggesting tumor infiltration by T cells as an element of mechanistic explanation. Increased expression of procoagulant genes, such as F3, was noted in recurrent compared to matched primary OSCC.

Conclusion

Our observations suggest that active coagulation shapes the oncological outcome of surgery. Analyzing the tumor procoagulant status might help predict postsurgical recurrence of OSCC.
Redirected walking method considering the interaction between users
Authors: Ri Sho , Matsumoto Keigo , Narumi Takuji , Kuzuoka Hideaki
Published: February 2025

Redirected walking (RDW), which enables users to walk in a larger virtual space than the physical space, is being applied to enable multiple people to perform activities in a vast VR space while avoiding collisions with each other in the same real space. A method called AFP-RDW, which uses scalar potentials, has been proposed as a control method for RDW. However, while the scalar potential can control the user’s position, it cannot control the user’s orientation. Therefore, APF-RDW cannot be directly used for interactions between users in situations where multiple people experience VR. In this study, we proposed a method to guide users to a position and posture where they can interact with each other by introducing artificial vector potentials (AVF) and walking path simulation. To verify the proposed method, we conducted simulation experiments assuming interaction with objects and other users, and the results suggest that users can interact with objects and other users in both physical and virtual spaces, even in VR experiences where multiple people share the physical and virtual spaces. The results suggest that users may be able to interact with objects, other users, and other users in VR experiences where multiple people share the physical and virtual spaces, respectively.
Emotional intelligence training in health students: a pilot study
Authors: Dugué Manon , Sirost Olivier , Heutte Natacha , Dosseville Fabrice
Published: February 2025

Introduction

The aim of this study was to test the effectiveness of an emotional intelligence (EI) program based on the tripartite model, combining theory and practical physical activity for health training students.

Method

This pilot study was conducted with 68 students between October 2020 and October 2021. One group received the EI training intervention (n = 34) combining 8 h of theory and 10 h of practical exercises with physical activities on different EC based on scientific literature. While the other group served as a control group (n = 34) and received an intervention on a topic other than emotional intelligence (i.e., sociological approach to the body) during 18 h (n = 34) Participants of both groups were required to complete the trait EI questionnaire in the pre and post-test.

Results

Results showed a significant increase in emotion expression, emotion identification, stress management, emotional management, emotional abilities, sociability and emotional intelligence. No significant change was observed in the control group.

Discussion

These findings suggest that EI can be improved with physical activities and open possibilities to include EI program in health training program.
Enhancing soil microbial diversity, quality, and crop growth through deficit irrigation combined with biochar application
Authors: Zhang Ruxin , Qu Zhongyi , Wang Liping , Yang Wei , Zhang Dongliang , Zhao Yibo , Li Junjie
Published: February 2025

Introduction

Biochar has been widely used under irrigation conditions because of its ability to improve agricultural soil productivity and crop yield. However, the effects of deficit irrigation biochar interactions on soil quality and underlying mechanisms remain not well understood.

Objective

This study aimed to determine whether deficit irrigation combined with biochar could interact with soil physics, chemistry, biology, and crop growth, thereby increasing the soil quality index and affecting crop yield and quality.

Methods

In this study, we conducted a 2-year experiment with differential irrigation: full irrigation (100% ETc) and deficit irrigation (60% ETc), applying three biochar doses (B0 = 0 t ha−1, B15 = 15 t ha−1, and B30 = 30 t ha−1).

Results

The results showed that the biochar and irrigation interaction significantly affected soil enzyme activities, nutrients, and microbial biomass carbon and adenosine triphosphate contents, resulting in an increase in the number of dominant taxa and α diversity index in the biochar treatment under deficit irrigation conditions. However, this treatment resulted in lower relative abundances of Acidobacteria, Chloroflexi, and Candidatus Rokubacteria. Biochar application improved sunflower kernel quality, aboveground biomass, and yield, with varying effects under different irrigation practices. Compared with the other treatments, the B30 treatment under deficit irrigation conditions exhibited the highest aboveground biomass and yield, with increases of 1.3–28.3% and 1.1–33.5%, respectively. However, an increase in arginine and proline contents in the seeds was only observed later in the experiment. In addition, the soil quality index was crucial for sunflower yield, with its positive effects varying based on the irrigation method used.

Conclusion

Biochar applied under deficit irrigation was effective in improving soil environment and soil quality in the study area, at least for the 2-year pilot study. Most importantly, biochar counteracted the adverse effects of water deficit and promoted crop seed quality and yield.

Significance

In conclusion, deficit irrigation combined with biochar application under conditions of water scarcity may be a novel approach for improving crop yield by reducing the negative effects of drought stress.
Different axis approaches for ultrasound-guided centrally inserted central catheterization in children: a systematic review and meta-analysis of randomized controlled trials
Authors: Lee In Kyung , Lee Kyeong Hun , Han Hye-ji , Choi Jieun , Kim Na Jin , Kim Kyunghoon
Published: February 2025

Background

Centrally inserted central catheterization (CICC) is a critical procedure in pediatric care. However, CICC in children poses greater challenges compared to adults due to anatomical and physiological differences, leading to higher complication rates. Ultrasound-guided approaches have been developed to enhance the safety and effectiveness of CICC, but the comparative efficacy of different axis approaches remains unclear.

Methods

A systematic review and meta-analysis of randomized controlled trials comparing different axis approaches for ultrasound-guided CICC in children was conducted. Searches were carried out in databases up to June 10, 2024. Six studies were included in the systematic review and three studies were included in the meta-analysis. Primary outcomes included first-attempt success rate, overall success rate, and cannulation time. Secondary outcomes were complications such as hematoma and posterior wall puncture.

Results

Data from 547 children were analyzed. The long-axis in-plane approach significantly reduced cannulation time (MD −27.48 s, 95% CI, −33.99 to −20.97) and overall complications OR 0.21, 95% CI, 0.1–0.48) compared to short-axis out-of-plane approach. No significant differences were found in first-attempt or overall success rates between the long-axis and short-axis approaches.

Conclusion

The long-axis approach for ultrasound-guided CICC in children offers significant advantages in reducing cannulation time and complications. While dynamic needle tip positioning method may serve as an alternative to in-plane methods, further studies are needed to validate its clinical efficacy. Further research is needed to refine these techniques and explore their application in diverse clinical settings.
Parametric Simulation Study of Liquid Film Cooling of Hydrocarbon Liquid Rocket Engine
Authors: Yang Huixin , Zou Haoyu , Song Zeming , Yu Wenhao
Published: February 2025

The hydrocarbon liquid rocket engine working environment is harsh; the thrust chamber needs to withstand high temperatures and a high-pressure working environment, and the thrust chamber wall material is difficult to bear, so it is necessary to design the cooling structure to reduce the gas damage to the chamber wall. Liquid film cooling is a common cooling method for hydrocarbon rocket engines, and numerical simulation is an important method for studying liquid film cooling. Most of the liquid film cooling numerical simulation is for a fixed model. This paper proposes a liquid film cooling numerical calculation method for a variable-configuration hydrocarbon liquid rocket engine, based on the secondary development of Fluent software (ANSYS Fluent 2022) to form a high-energy hydrocarbon liquid rocket engine design software, which can be realized on the Qt platform. The visualization interface can be for different engine injection port locations, numbers, angles, mass flow rates, and other parameters, to calculate and improve design efficiency and reduce operating difficulty.
Rabbit Resilience Selection Alters Embryo Development and Modifies Metabolic Profiles of Organic Acid and Glucose
Authors: García María-Luz , Hadjadj Inmane , Agea Iván , Argente María-José
Published: February 2025

A divergent selection for resilience was carried out in rabbits over 12 generations. The selection criterion was increased (the HO line) and decreased litter size variability at birth (the HE line). The HO line (more resilient) shows higher litter size than the HE line (less resilient). The HO line sows higher litter size and embryo development than the HE line. The aim of this work is to investigate the plasma organic acid profile in both lines at mating and early gestation in order to analyze the effect of selection by resilience in the ovulation rate and early gestation. A total of 19 and 18 nonlactating multiparous females from the HE and HO lines were used. The ovulation rate, normal embryos, and percentage of compacted morulae at 72 h post-coitum (hpc) were studied, and blood samples were obtained at mating and 72 hpc. The organic profile was determined by HPLC. Bayesian methodology was used for statistical analysis. The HE line had 1.5% fewer normal embryos and 12.3% fewer compacted morulae than the HO line. The ovulation rate was similar in both lines. α-ketoglutaric acid and cis-aconitic acid were higher in the HE line than in the HO line. Citric acid, lactic acid, and pyruvic acid were higher at mating than at early gestation. In conclusion, the lower efficiency in the utilization of energy sources in the HE line could explain the reduced embryo production observed. The organic profile varies depending on the reproductive state in the female.
RDRM-YOLO: A High-Accuracy and Lightweight Rice Disease Detection Model for Complex Field Environments Based on Improved YOLOv5
Authors: Li Pan , Zhou Jitao , Sun Huihui , Zeng Jian
Published: February 2025

Rice leaf diseases critically threaten global rice production by reducing crop yield and quality. Efficient disease detection in complex field environments remains a persistent challenge for sustainable agriculture. Existing deep learning-based methods for rice leaf disease detection struggle with inadequate sensitivity to subtle disease features, high computational complexity, and degraded accuracy under complex field conditions, such as background interference and fine-grained disease variations. To address these limitations, this research aims to develop a lightweight yet high-accuracy detection model tailored for complex field environments that balances computational efficiency with robust performance. We propose RDRM-YOLO, an enhanced YOLOv5-based network, integrating four key improvements: (i) a cross-stage partial network fusion module (Hor-BNFA) is integrated within the backbone network’s feature extraction stage to enhance the model’s ability to capture disease-specific features; (ii) a spatial depth conversion convolution (SPDConv) is introduced to expand the receptive field, enhancing the extraction of fine-grained features, particularly from small disease spots; (iii) SPDConv is also integrated into the neck network, where the standard convolution is replaced with a lightweight GsConv to increase the accuracy of disease localization, category prediction, and inference speed; and (iv) the WIoU Loss function is adopted in place of CIoU Loss to accelerate convergence and enhance detection accuracy. The model is trained and evaluated utilizing a comprehensive dataset of 5930 field-collected and augmented sample images comprising four prevalent rice leaf diseases: bacterial blight, leaf blast, brown spot, and tungro. Experimental results demonstrate that our proposed RDRM-YOLO model achieves state-of-the-art performance with a detection accuracy of 94.3%, and a recall of 89.6%. Furthermore, it achieves a mean Average Precision (mAP) of 93.5%, while maintaining a compact model size of merely 7.9 MB. Compared to Faster R-CNN, YOLOv6, YOLOv7, and YOLOv8 models, the RDRM-YOLO model demonstrates faster convergence and achieves the optimal result values in Precision, Recall, mAP, model size, and inference speed. This work provides a practical solution for real-time rice disease monitoring in agricultural fields, offering a very effective balance between model simplicity and detection performance. The proposed enhancements are readily adaptable to other crop disease detection tasks, thereby contributing to the advancement of precision agriculture technologies.
Risk Assessment and Fitness Cost of Tetraniliprole Resistance in Ostrinia furnacalis (Lepidoptera: Crambidae)
Authors: Xu Tingting , Hu Fei , Yue Ran , Hu Benjin , Bi Sijia , Tong Youmin , Xu Lina
Published: February 2025

Asian corn borer (ACB), Ostrinia furnacalis, is a predominant pest species that is widely distributed across major corn-growing regions in China. Tetraniliprole, a novel diamid insecticide, exhibited good efficacy on lepidopteran insect pests and was officially sanctioned for controlling ACB in China. In this study, a tetraniliprole-resistant strain called ACB-TLR was obtained from a susceptible strain, ACB-SS, after 10 continuous generation selections with tetraniliprole. Additionally, the fitness cost of the ACB-TLR strain was assessed. The results showed that ACB developed 11.58-fold resistance to tetraniliprole and the realized heritability was estimated as 0.213. The ACB-TLR strain displayed 2.10 times cross-resistance to chlorantraniliprole, but we found no cross-resistance to emamectin benzoate and deltamethrin. The development time of larvae and pupae was significantly prolonged, the adult longevity was significantly shorter, and the pupation and emergence rates were significantly reduced in the ACB-TLR strain than in the ACB-SS strain, with a relative fitness of 0.39. The current study indicated that ACB has the potential to develop resistance to tetraniliprole in the field. However, the decreased fitness may allow insecticide resistance to be managed.
Construction of Genetic Linkage Maps Using SSR Markers and Identification of Flower Bud-Related QTLs in Nightlily (Hemerocallis citrina)
Authors: Hou Feifan , Liang Xufei , Chen Rui , Ji Xuan , Li Hongtao , Jing Mengyue , Gao Yang , Liu Yuting , Li Sen , Xing Guoming , Wang Yanfang
Published: February 2025

Nightlily (Hemerocallis citrina Baroni) is an important vegetable with edible floral organs. It possesses considerable economic value due to its edibility, ornamental, and medicinal properties. However, the genetic linkage map construction and quantitative trait locus (QTL) mapping of nightlily have not been performed. This study used two varieties ‘Dongzhuanghuanghua’ and ‘Chonglihua’ of nightlily as cross parents to establish an intraspecific hybridization population of 120 F1 progenies. The ‘Datonghuanghua’ (female) variety of nightlily and ‘Lullaby Baby’ (male) variety of daylily were selected to construct an interspecific hybridization population of 55 F1 progenies. A total of 965 expressed sequence tag–simple sequence repeats (EST-SSRs), along with 20 SSR markers from various sources, were used for genetic mapping. Among these markers, CT/TC (9.24%) of the dinucleotide and GGA/GAG/AGG (4.67%) of the trinucleotide repeat motifs were most abundant. In the intraspecific hybridization genetic map, a total of 124 markers were resolved into 11 linkage groups, with a total map length of 1535.07 cM and an average interval of 12.38 cM. Similarly, the interspecific hybridization map contained 11 linkage groups but with 164 markers, a total map length of 2517.06 cM, and an average interval of 15.35 cM. The two constructed maps had 48 identical markers and demonstrated good collinearity. The collinearity analysis showed that 161 markers hit the genomic sequence of the published H. citrina genome, indicating that the two constructed genetic maps had high accuracy. Phenotypic data were investigated over two consecutive years (2018 and 2019) for flower bud fresh weight, dry weight, and bud length in two hybridization populations. A total of nine QTLs associated with flower bud-related traits were identified, among which those located on linkage group 8 of the intraspecific genetic map and linkage group 4 of the interspecific genetic map showed good stability. All nine QTLs had LOD values of not less than 4 and PVE values of not less than 15% over two years. This is the first report about the intra- and interspecific genetic map construction and QTL mapping of the flower bud-related traits in nightlily based on a genetic map. The results promote marker-assisted breeding and offer insights into the mechanisms underlying important traits of the genus Hemerocallis.
Oat Ears Detection and Counting Model in Natural Environment Based on Improved Faster R-CNN
Authors: Tian Cong , Wang Jiawei , Zheng Decong , Li Yangen , Zhang Xinchi
Published: February 2025

In order to enable oat ears to be quickly and accurately identified in the natural environment, this paper proposes an oat ears detection and counting model based on an improved Faster R-CNN. In the backbone network, the commonly used single convolutional neural network is replaced by a parallel convolutional neural network to realize the feature extraction of oat ears, and a feature pyramid network (FPN) is incorporated to improve the small target-missed detection problem and the multi-scale problem of oat ears. Then, the anchor box configuration is optimized according to the size and distribution of the labeled boxes in the dataset, which improves the efficiency of the model to detect oat ears. Finally, progressive non-maximum suppression (Progressive-NMS) was used to replace non-maximum suppression (NMS) to optimize the screening process of prediction boxes. According to the data from different experiments designed, the optimized model can effectively detect oat ears in the natural environment and complete the counting of oat ears per unit area. Compared with the traditional Faster R-CNN detection model, the mean average precision (mAP) of the improved model is increased by 13.01%, which could provide reference for oat yield prediction and intelligent operation.
The Influence of Planting Method and Short-Term Organic Amendments on Rhizosphere Microbial Communities in Paddies: Preliminary Results
Authors: Liu Ziqi , Tang Zhiqiang , Wang Lili , Wen Li , Liang Yi , Wang Changhua , Wang Hui
Published: February 2025

This study assessed the impact of planting techniques and short-term organic additions on soil quality, enzyme activity, and bacterial community composition. Biochar (BC) amendment substantially enhanced the ACE, Chao 1, and Shannon indices in direct-seeded rice (DS). Principal coordinate analysis (PCoA) and dissimilarity distances confirmed significant differences in the rhizosphere bacterial community composition associated with planting methods and organic applications. At the phylum level, transplanting (TT) significantly increased the abundance of Proteobacteria, Planctomycetes, Bacteroidetes, Firmicutes, and Verrucomicrobia, whereas DS significantly reduced the abundance of Acidobacteria, Chloroflexi, Actinobacteria, Gemmatimonadetes, and WPS-2. Rice straw (RS) application was associated with increased Proteobacteria, Acidobacteria, Chloroflexi, and Gammaproteobacteria, while BC application improved Bacteroidetes, Firmicutes, and Verrucomicrobia. Planting methods and organic amendments were also observed to affect soil enzyme activities and physicochemical properties. DS was associated with an increase in microbial biomass nitrogen (MBN) and carbon (MBC), cellulase activities (CA), total phosphorus (TP), available nitrogen (AN), and available potassium (AK), while TT significantly increased urease activities (UA). Compared to BC and the control (CK), RS significantly increased CA, AN, and available phosphorus (AP). RDA ordination plots were used to examine the interactions between soil bacterial communities and soil physicochemical properties; planting techniques and organic additions had different effects on soil bacterial communities. Compared to RS and CK, BC enhanced MBN, MBC, UA, and AK. According to Pearson’s correlation analysis, Chloroflexi levels were positively associated with those of organic carbon (OC), MBN, and MBC. OC, TP, MBN, and CA positively correlated with gemmatimonadetes. In conclusion, these data reveal that planting practices and short-term organic inputs alter soil’s physicochemical parameters, enzyme activity, and microbial community composition.
Effect of Lime, Mineral Fertilizer and Manure on Soil Characteristics and Yield of Four Maize Hybrids
Authors: Dugalić Marijana , Rakočević-Bošković Ljiljana , Latković Dragana , Rajičić Vera , Terzić Dragan , Životić Ljubomir
Published: February 2025

Pseudogley soils in Serbia are characterized by poor chemical and physical properties that limit maize yields. Nevertheless, they are still used on large areas due to their favorable topographic position and lack of better-quality soils. It is common practice to regularly apply mineral fertilizers to these soils, but this does not increase maize yields to an economically sufficient level, although the doses are increased. At the same time, the inappropriate application of mineral fertilizers deteriorates soil chemical properties. Lime is only moderately used in Serbia despite its known benefits, whereas manure is not satisfactorily used. Therefore, a two-factorial experiment was set up as a randomized block design with three replications and conducted near Kraljevo, Serbia, to investigate the effect of mineral fertilizers, manure and lime on maize growth. The experiment included three fertilization regimes: F—application of common fertilizer doses, LF—application of the same fertilizer doses with 3 t·ha−1 of lime, and LMF—application of the same fertilizer doses with lime and 30 t·ha−1 of manure. The response of four maize hybrids to different fertilization practices was investigated. The soil was acid, poor in humus, and contained an increased content of mobile aluminum. There was a significant increase in the 3-year average yield of all hybrids in LMF- and LF-treatments compared with F-treatment, 30.7 and 25.6%, respectively. The increase in yield was accompanied by an improvement in soil chemical properties after three years, i.e., increased soil reaction in LF- and LMF-treatments, increased content of available phosphorus, an increase in base saturation by 61 and 75%, and aluminum immobilization by 2.55 and 4.19 fold, respectively, compared to initial conditions. The hybrid NS 640 demonstrated the highest yield when only mineral fertilizers were used, which indicated its tolerance to the unfavorable physical and chemical soil properties and suggested that it can be recommended for growing on pseudogleys without applying amelioration practices. The hybrids NS 6030 and ZP 606 achieved statistically significantly higher yields than the other hybrids when lime and manure were applied, which indicates that adequate fertilization coupled with soil improvement practices should be used in order to achieve satisfactory yields. The obtained results showed that liming can be considered as a longer-term sustainability practice in maize production in Serbia on pseudogley soils, and that there is an array of maize hybrids which can be grown depending on management strategies applied.
Biocontrol Activity of Alternaria angustiovoidea Against Trichothecium roseum Through Inhibiting Its Growth, Pathogenicity, and Gene Expression
Authors: Guo Xiuna , Xu Meiting , Wang Shaoli , Zhang Wei , Liu Baoyou
Published: February 2025

Apple mold heart disease, primarily caused by Trichothecium roseum, is the most severe disease affecting stored apples. Developing biocontrol resources as an alternative to chemical pesticides is crucial for the advancement of green agriculture. This study demonstrated that a pathogenic fungus isolated from sunflower leaves exhibited specific inhibitory effects against T. roseum. Through morphological observation, identification, and the construction of a phylogenetic tree analysis, the fungus was identified as Alternaria angustiovoidea. GW2A was found to inhibit the spread of diseases on apple twigs. Additionally, GW2A has significant preventive and therapeutic effects on apple mold heart disease. Furthermore, GW2A can induce apple trees to upregulate defense-related genes, thereby enhancing resistance. Transcriptome analysis revealed that GW2A inhibits T. roseum growth by suppressing the function of polysaccharide hydrolases, oxidoreductases, and intermediate steps in carbohydrate metabolism. In conclusion, our research has effectively isolated and characterized A. angustiovoidea, revealing its significant potential as a biocontrol agent against T. roseum and apple mold heart disease, particularly in areas where sunflowers and apple trees are not co-cultivated. Additionally, we demonstrated its ability to induce resistance in apple trees, offering a sustainable approach to disease management in apple cultivation.
Morphological Analysis and Subtype Detection of Acute Myeloid Leukemia in High-Resolution Blood Smears Using ConvNeXT
Authors: Mustapha Mubarak Taiwo , Ozsahin Dilber Uzun
Published: February 2025

(1) Background: Acute Myeloid Leukemia (AML) is a complex hematologic malignancy where accurate subtype classification is crucial for targeted treatment and improved patient outcomes. Automated AML subtype detection is especially important for underrepresented subtypes to ensure equitable diagnostics; (2) Methods: This study explores the potential of ConvNeXt, an advanced convolutional neural network architecture, for classifying high-resolution peripheral blood smear images into AML subtypes. A deep learning pipeline was developed, integrating Stochastic Weight Averaging (SWA) for model stability, Mixup data augmentation to enhance generalization, and Grad-CAM for model interpretability, ensuring biologically meaningful feature visualization. Various models, including ResNet50 and Vision Transformers, were benchmarked for comparative performance analysis; (3) Results: ConvNeXt outperformed ResNet50, achieving a classification accuracy of 95% compared to 91% for ResNet50 and 81% for transformer-based models (Vision Transformers). Grad-CAM visualizations provided biologically interpretable heatmaps, enhancing trust in computational predictions and bridging the gap between AI-driven diagnostics and clinical decision-making. Ablation studies highlighted the contributions of data augmentation, optimizer selection, and hyperparameter tuning, demonstrating the robustness and adaptability of the model; (4) Conclusions: This study advances AI’s role in hematopathology by combining high classification performance, explainability, and scalability. ConvNeXt offers a robust, interpretable, and scalable solution for AML subtype classification, improving diagnostic precision and supporting clinical decision-making. These results underscore the potential for AI-driven advancements in equitable and efficient AML diagnostics.
Longitudinal Study on the Effect of Season and Weather on the Behaviour of Domestic Cats (Felis catus)
Authors: Smit Michelle , Andrews Christopher J. , Draganova Ina , Corner-Thomas Rene A. , Thomas David G.
Published: February 2025

To date, little is known about seasonal changes in specific cat behaviours, and how these are affected by weather patterns. Using accelerometer data and a validated machine learning model, behaviours including being active, eating, grooming, littering, lying, scratching, sitting, and standing were quantified for seven research cats for a total of 13 weeks spread over one year, with weather data being collected simultaneously. Generalised linear mixed models were used to statistically test for seasonal differences in proportional behavioural data and how behaviour was affected by weather variables. Seasonal differences were found for time spent eating (p < 0.001), grooming (p < 0.001), littering (p = 0.037), lying (p < 0.001), scratching (p < 0.001), and sitting (p < 0.001) but not for active behaviours and standing (p > 0.05). A positive interaction effect of the temperature humidity wind index and daylength was found for time spent eating, lying, and standing (all p < 0.001), while it was negative for active (p < 0.001), grooming (p < 0.001), littering (p = 0.004), and sitting (p < 0.001). Rainfall negatively affected grooming (p = 0.023) and scratching (p = 0.037). These findings highlight seasonality in cat behaviours, influenced by weather conditions.
Genetic Analysis of Litter Size Across Parities in Prolific and Conventional Populations of Tunisian Barbarine Sheep Using a Random Regression Model
Authors: Ziadi Chiraz , Serradilla Juan Manuel , Bedhiaf-Romdhani Sonia , Molina Antonio
Published: February 2025

Litter size records from two lines of Tunisian Barbarine sheep were analysed across parities using an RRM. A total of 2751 and 2562 litter records from the first to the sixth parity from the prolific and the conventional lines, respectively, were included in the analysis. The total number of animals in the pedigree was 1277 for the prolific line and 1102 for the conventional line. The estimation of genetic parameters was based on Bayesian inference under categorical distribution. Fixed effects included the year and month of lambing and a fixed quadratic regression coefficient for the lambing number with Legendre polynomials. The random additive and permanent environmental effects were modelled by second-order Legendre polynomials. Heritability ranged from 0.04 to 0.18 for the prolific line and from 0.17 to 0.39 for the conventional line. Genetic correlations within trait through parities showed a wide range of values, from 0.25 to 0.96 for the prolific line and from zero to 0.93 for the conventional line. Due to the changes in the variances and the genetic correlations different from unity across parities, the use of an RRM is recommended to analyse litter size in the Barbarine sheep.
Body Temperature Detection of Group-Housed Pigs Based on the Pairing of Left and Right Ear Roots in Thermal Images
Authors: Xiang Rong , Zhang Yi , Lin Hongjian , Fu Yingchun , Rao Xiuqin , Pan Jinming , Pan Chenghao
Published: February 2025

Body temperature is a critical indicator of pig health. This study proposes a non-contact method for detecting body temperature in group-housed pigs by extracting temperature data from thermal images of ear roots. Thermal images in the drinking trough area were captured using a thermal camera, with real-time data transmitted to a monitoring room via optical fibers. The YOLO v11m-OBB model was utilized to detect the ear root areas with oriented bounding boxes, while a novel algorithm, the two-stage left and right ear root pairing algorithm (YOLO TEPA-OBB), paired the ear roots of individual pigs using center distance clustering and angular relationships in a polar coordinate system. The maximum temperature of the ear roots was extracted to represent the body temperature. Experimental results based on 749 ear roots show that the YOLO TEPA-OBB achieves 98.7% precision, 98.4% recall, and 98.7% mean average precision (mAP) in detecting ear roots, with an ear root pairing accuracy of 98.1%. The Pearson correlation coefficient (r) between predicted and reference temperatures is 0.989, with a mean bias of 0.014 °C and a standard deviation of 0.103 °C. This research facilitates real-time body temperature monitoring and precise health management for group-housed pigs.
Molecular Characterization of BsCu/Zn-Superoxide Dismutases and BsMn-Superoxide Dismutases from Chinese Black Sleeper (Bostrychus sinensis)
Authors: Li Haolin , Ran Suzhen , Wang Xiaoyu , Shen Bin , Zhang Jianshe
Published: February 2025

Superoxide dismutases (SODs) are critical antioxidant enzymes that protect organisms by catalyzing the dismutation of superoxide radicals into molecular oxygen (O2) and hydrogen peroxide (H2O2). In this study, we cloned the full-length cDNA of two SODs (BsCu/Zn-SOD and BsMn-SOD) from the Chinese black sleeper. The cDNA of BsCu/Zn-SOD consists of 465 nucleotides encoding 154 amino acids, while the BsMn-SOD comprises 678 nucleotides encoding 225 amino acids. The PCR results indicated that in normal tissues, the highest expression of BsCu/Zn-SOD (1.02-fold) was primarily observed in muscle, whereas the highest expression of BsMn-SOD (6.42-fold) was noted in skin. Following treatment with Vibrio parahaemolyticus, the highest expression of BsCu/Zn-SOD (3.67-fold) was detected in the spleen, while BsMn-SOD (3.36-fold) presented the highest expression in the blood. After poly(I:C) treatment, the highest expression of BsCu/Zn-SOD (2.92-fold) was found in the blood, with BsMn-SOD (2.37-fold) showing the highest expression in the spleen. Following Cd2+ treatment, the highest expression of BsCu/Zn-SOD (3.36-fold) was recorded in the liver at the 1/2 96 h LC50 concentration, and in the spleen at both the 1/4 96 h LC50 (2.50-fold) and 1/8 96 h LC50 concentrations. In contrast, BsMn-SOD presented the highest expression (2.60-fold) in the liver across all three concentrations. These findings suggest that both BsCu/Zn-SOD and BsMn-SOD play vital roles in the innate immune response to environmental challenges, laying the foundation for further exploration of antioxidant mechanisms.
A Comparison of the Application of Load Monitoring Metrics for Key Match Characteristics in Women’s Rugby Sevens
Authors: Epp-Stobbe Amarah , Tsai Ming-Chang , Klimstra Marc
Published: February 2025

In rugby sevens, multiple high-speed matches in quick succession make effective workload monitoring essential to support decision-making around athlete preparedness and competition strategy. Match characteristics like score differential, player’s competition experience, match type, and opponent may influence workload. The purpose of this investigation was to examine the relationships between match and player characteristics and three workload measures, session rating of perceived exertion (sRPE), mechanical work, and an alternative speed–deceleration–contact (SDC) model. Twenty-two female rugby sevens athletes were monitored across 103 international matches. Data from GNSS-derived playing times, speeds, accelerations, athlete mass, and self-reported ratings of perceived exertion were collected. sRPE and mechanical work were computed, and the SDC model produced predicted values. Associations between player experience, game category, opponent rank, and score differential with each workload measure were tested using ANOVAs with Tukey’s post hoc test. Player experience and match category were significant for all three workload measures. Opponent was significant associated with sRPE and the SDC model, and match outcome was only associated with sRPE. All three workload measures, sRPE, mechanical work, and the SDC model, are valuable but differ in response to contextual and experiential factors.
Designing a Conceptual Digital Twin Architecture for High-Temperature Heat Upgrade Systems
Authors: Matei Alexandru , Butean Alex , Zamfirescu Constantin-Bala , Marcos José Daniel
Published: February 2025

Industrial processes often rely on high-temperature heat, traditionally generated through the combustion of fossil fuels. However, a significant shift towards renewable and sustainable heat sources is underway, supported by environmental policies and actions such as the European Green Deal. These renewable energy systems are complex and characterized by a high degree of interdependencies between various parameters. Optimizing and orchestrating these processes for efficient heat delivery requires careful consideration of factors such as temperature levels, flow rates, and energy demands. Traditional methods often struggle to handle the complexity of these systems, hindering efforts to maximize efficiency and minimize energy waste. This paper addresses these challenges by proposing a modular digital twin framework tailored for high-temperature heat upgrade systems. By integrating with the physical heat upgrade system, the digital twin can create a dynamic and continuously updated representation of its behavior, while also providing additional advantages such as improved process simulation, predictive capabilities, enhanced design, and system integration. Using the SUSHEAT project as a case study, this work advances digital twin methodologies by introducing an architecture applicable in the early product lifecycle phases, addressing a gap in current research.
Characterization of the Evolution of Energy Loss Rate in Cyclic Load Testing of Marine Soft Soil
Authors: Sun Yindong , Zhang Heng , Liu Yajun , Wu Ke , Zheng Yang
Published: February 2025

The study of energy evolution laws has been widely applied in the geotechnical analysis of soft rocks and coal seams. However, research on marine soft soil has primarily focused on consolidation behavior, shear properties, and microstructural evolution, with limited exploration of systematic methods based on energy evolution laws. This paper addresses this gap by analyzing dynamic triaxial test data to explore the relationship between energy loss rate and the number of cyclic loadings in marine soft soil. Through energy loss calculations and derivations, a mathematical expression for the energy loss rate is established using curve fitting. Additionally, an envelope diagram depicting the energy dissipation rate of marine soft soil under varying perimeter pressures and water contents is presented. This diagram serves as a criterion for assessing the stability of marine soft soil, which is further validated through engineering applications. The findings offer novel approaches and insights for developing theoretical models and rapid strength assessment techniques for marine soft soil in engineering practices.
Physics-Based Noise Modeling and Deep Learning for Denoising Permanently Shadowed Lunar Images
Authors: Pan Haiyan , Chen Binbin , Zhou Ruyan
Published: February 2025

The Narrow-Angle Cameras (NACs) onboard the Lunar Reconnaissance Orbiter Camera (LROC) capture lunar images that play a crucial role in current lunar exploration missions. Among these images, those of the Moon’s permanently shadowed regions (PSRs) are highly noisy, obscuring the lunar topographic features within these areas. While significant advancements have been made in denoising techniques based on deep learning, the direct acquisition of paired clean and noisy images from the PSRs of the Moon is costly, making dataset acquisition expensive and hindering network training. To address this issue, we employ a physical noise model based on the imaging principles of the LROC NACs to generate noisy pairs of images for the Moon’s PSRs, simulating realistic lunar imagery. Furthermore, inspired by the ideas of full-scale skip connections and self-attention models (Transformers), we propose a denoising method based on deep information convolutional neural networks. Using a dataset synthesized through the physical noise model, we conduct a comparative analysis between the proposed method and existing state-of-the-art denoising approaches. The experimental results demonstrate that the proposed method can effectively recover topographic features obscured by noise, achieving the highest quantitative metrics and superior visual results.
Improved Efficiency of Lutein Extraction from Hens’ Feed Mixture and Food Samples Using Less Toxic Solvent Mixture
Authors: Galović Olivera , Prokopec Doris , Kralik Zlata , Košević Manuela , Kralik Gordana
Published: February 2025

Lutein is one of the nutrients necessary for the proper functioning of our organism. The majority of research focuses on the impact of lutein on eye health and its role as an antioxidant. Although fruits and vegetables are the most important sources of lutein, chicken eggs are considered an excellent and widely used source, necessitating the determination of lutein concentration in food. One of the methods for extracting lutein from various food samples is solvent extraction. Although it is one of the older methods and has disadvantages compared to instrumental methods, it is still widely used. In this investigation, the adapted AOAC method developed by Leeson et al. (used here as a standard method), was modified by adjusting the composition of the extraction solvent mixture in order to reduce the amount of toxic solvents used. The mixture of hexane:acetone:ethanol:toluene (10:7:6:7, v/v/v/v) was replaced with a mixture of methanol:acetone (1:1, v/v). The concentration of lutein extracted from the hens’ feed mixture was 52% higher compared to the method developed by Leeson et al. The suitability of the modified method was tested on two parallel samples, and the obtained recovery values were 95.68% and 98.38%, respectively. The influence of ultrasound on lutein extraction was examined, but the obtained concentration of lutein was 8.66% lower than the concentration determined by the modified standard method. The modified standard method was then used to determine lutein concentration in six hens’ feed mixture samples and eight food samples. The results obtained were in accordance with the data from the literature.
Water Segmentation for Unmanned Ship Navigation Based on Multi-Scale Feature Fusion
Authors: Han Xin , Yuan Yifeng , Zhong Jingzhi , Deng Junlin , Wu Ning
Published: February 2025

The segmentation of the navigation area from water images is of great significance in the safe and automated navigation of unmanned vessels. However, accurate segmentation of water boundaries in real time under the interference of water-surface light changes is still a challenging problem. In this study, a river water segmentation method based on a multi-scale feature fusion network (Fuse-ResNet), which improves the segmentation of river water boundaries by focusing more on the target features, is proposed. An Atrous Spatial Pyramid Pooling (ASPP) mechanism is introduced to expand the sensory field and enhance the relevance of contextual information at different scales. Experimental results based on the USVInland unmanned vessel dataset show that the proposed method achieves a mean Pixel Accuracy (mPA) of 99.25% and a mean Intersection over Union (mIoU) of 98.45% in the water category, which are better than those achieved by mainstream models. The interference of background noise resulting from water surface reflection can be suppressed to improve the accuracy of water segmentation for unmanned vessel navigation.