bluuebunny/crossref_metadata_2025 huggingface dataset:
DHS-YOLO: Enhanced Detection of Slender Wheat Seedlings Under Dynamic Illumination Conditions
Authors: Dong Xuhua , Pan Jingbang
Published: February 2025

The precise identification of wheat seedlings in unmanned aerial vehicle (UAV) imagery is fundamental for implementing precision agricultural practices such as targeted pesticide application and irrigation management. This detection task presents significant technical challenges due to two inherent complexities: (1) environmental interference from variable illumination conditions and (2) morphological characteristics of wheat seedlings characterized by slender leaf structures and flexible posture variations. To address these challenges, we propose DHS-YOLO, a novel deep learning framework optimized for robust wheat seedling detection under diverse illumination intensities. Our methodology builds upon the YOLOv11 architecture with three principal enhancements: First, the Dynamic Slender Convolution (DSC) module employs deformable convolutions to adaptively capture the elongated morphological features of wheat leaves. Second, the Histogram Transformer (HT) module integrates a dynamic-range spatial attention mechanism to mitigate illumination-induced image degradation. Third, we implement the ShapeIoU loss function that prioritizes geometric consistency between predicted and ground truth bounding boxes, particularly optimizing for slender plant structures. The experimental validation was conducted using a custom UAV-captured dataset containing wheat seedling images under varying illumination conditions. Compared to the existing models, the proposed model achieved the best performance with precision, recall, mAP50, and mAP50-95 values of 94.1%, 91.0%, 95.2%, and 81.9%, respectively. These results demonstrate our model’s effectiveness in overcoming illumination variations while maintaining high sensitivity to fine plant structures. This research contributes an optimized computer vision solution for precision agriculture applications, particularly enabling automated field management systems through reliable crop detection in challenging environmental conditions.
Effect of Dietary Addition of Lentinus edodes on Rumen Flora, Lactation, and Health of Dairy Goats
Authors: Shen Huijun , Wang Mengyu , Ning Yong , Zhao Yiqi , Danzeng Baiji , Li Kaixin , Shi Huaiping , Li Weijuan
Published: February 2025

Lentinus edodes (LE) is a nutrient-rich medicinal fungus with potential applications in animal nutrition; however, its effects on dairy goats remain underexplored. This study investigated the impact of dietary LE addition on rumen microbiota, metabolic profiles, serum immunity, and milk quality in lactating dairy goats. Twenty Saanen goats were randomly assigned to a control group (CON, basal diet) or an LE group (basal diet + 25 g Lentinus edodes) for 56 days. Rumen fluid, serum, and milk samples were analyzed using 16S rDNA sequencing, metabolomics, and biochemical assays. The results showed that the addition of LE altered the microbial composition, decreasing the abundance of fibrobacterial flora and Treponema (p < 0.05) while increasing VadinHA49. Metabolomic analysis revealed elevated fumaric acid, lysophospholipids (LysoPE, LysoPG), and D-quinic acid in the rumen (p < 0.05). Serum immunoglobulin A (IgA), immunoglobulin G (IgG), total antioxidant capacity (T-AOC), superoxide dismutase (SOD), catalase (CAT), and tumor necrosis factor-α (TNF-α) levels were significantly enhanced (p < 0.05). The milk somatic cell count (SCC) was reduced by 52.8% (p = 0.005) at day 56, and protein, fat, and total solids increased significantly (p < 0.05). Enrichment of functional metabolites such as D-arabitol and D-tryptophan in milk further highlighted LE’s role in improving product value. These findings demonstrate that LE optimizes rumen flora, enhances antioxidant and immune functions, and improves milk quality, supporting its use as a functional feed additive for dairy goats.
Animals for the Deceased: Zooarchaeological Analysis of the Bronze Age in the Castillejo del Bonete Site (Terrinches, Ciudad Real, Spain)
Authors: Galindo-Pellicena María Ángeles , Pérez-Romero Amalia , Gómez-Felipe Andrea , Romero-Ruiz Marta , Blázquez-Orta Raquel , Andreu-Alarcón Silvia , Benítez de Lugo Enrich Luis
Published: February 2025

The 2978 faunal bone remains recovered from the Bronze Age levels at the Castillejo del Bonete site between 2005 and 2019 were analyzed in this study. In the main structure (Great Tumulus 1, Tumulus 2, and Tomb 5), the faunal bone remains were identified and interpreted as offerings in a funerary context. In Enclosure 4, a large building possibly dedicated to the celebration of wakes and rituals—including the eating of food and drinking—in honor of the deceased, the anthropic modifications on the bone surfaces indicate their possible consumption. The cave is constituted by four galleries with inhumations (in Galleries 2, 3, and 4) and pithoi (in Gallery 4). Wild and domestic animals were identified in the cavity, and the caprine (likely sheep) is the best represented taxa in the entire cave. The almost complete skeletal representation; the predominance of fetal, neonate, and juvenile individuals; the absence of anthropic modifications related to consumption, in addition to the bone industry made of caprine bones (such as an eye idol and anthropomorphic artefacts), suggest that caprines were used as offerings to the deceased that accompany them. Postdepositional taphonomic alterations, the animals not having been found in anatomical connection, and the refits of the bones between different stratigraphical units indicate the repeated use of the cave during the Bronze Age.
Vertebral Heart Score and Vertebral Left Atrial Size as Radiographic Measurements for Cardiac Size in Dogs—A Literature Review
Authors: Baisan Radu Andrei , Vulpe Vasile
Published: February 2025

Radiology plays an important role in veterinary cardiology, along with other methods, such as electrocardiography, echocardiography, and biomarkers, in the diagnosis of cardiac diseases. Particularly, thoracic radiography is often used to assess heart size and for confirmation of left-sided congestive heart failure by the presence of pulmonary edema. Many cardiac diseases in dogs are associated with a heart size increase, especially in more advanced stages, and cardiac size assessment has been of great interest for a long time for both clinicians and researchers. A substantial number of methods for heart size measurement has been described; however, two methods, the vertebral heart score and the vertebral left atrial size are currently widely used in dogs. Therefore, the literature provides an abundant number of research articles for using these measurements in both healthy dogs and dogs with cardiac and extra-cardiac pathologic conditions. This review article aims to cover the current use of two radiographic measurements of the heart in healthy and diseased dogs, based on the available literature.
Pharmacokinetic Characteristics of Tolfenamic Acid in Freshwater Crocodiles (Crocodylus siamensis)
Authors: Laut Seavchou , Poapolathep Saranya , Khidkhan Kraisiri , Klangkaew Narumol , Phaochoosak Napasorn , Wongwaipairoj Tara , Giorgi Mario , Escudero Elisa , Marin Pedro , Poapolathep Amnart
Published: February 2025

The present study was undertaken to characterize the plasma kinetic disposition of tolfenamic acid (TA) in freshwater crocodiles. In total, 15 freshwater crocodiles were used in the experiment and randomly divided into three groups, with TA administered at 2 mg/kg body weight (b.w.) intravenously (IV) or at 2 or 4 mg/kg b.w. intramuscularly (IM). Blood samples were collected at predetermined times up to 168 h after IV or IM drug administration. Plasma concentrations of TA were determined using validated high-performance liquid chromatography with a UV detector and then analyzed based on the non-compartmental method. The maximum concentration values of TA were 3.03 µg/mL and 6.83 µg/mL following IM administration at a dose of 2 mg/kg b.w. or 4 mg/kg b.w., respectively. The elimination half-lives were 21.89 h (2 mg/kg; IV), 17.74 h (2 mg/kg; IM), and 13.57 h (4 mg/kg; IM). Following IV administration, the volume of distribution and clearance were 1.58 L/kg and 50.04 mL/h/kg, respectively. The absolute IM bioavailability was 71.0% at a dose of 2 mg/kg b.w. and 92.63% at a dose of 4 mg/kg b.w. The average ± SD of plasma protein binding of TA was 26.15 ± 4.93%. Good bioavailability levels and favorable plasma concentrations of TA were obtained in freshwater crocodiles after IM administrations, considering that this is the preferred route of drug administration in freshwater crocodiles. Multi-dose and pharmacodynamic studies are needed to better establish the safety and efficacy of using TA in this crocodilian species.
Effect of Supplemental Trace Mineral Source on Haircoat and Activity Levels in Senior Dogs
Authors: Amundson Laura A. , Millican Allison A. , Swensson Erik , McGilliard Mike L. , Tomlinson Dana
Published: February 2025

Trace minerals (TMs) are pivotal for animal wellbeing and appearance. This study evaluated the effects of TM (Zn, Mn, Cu, and Fe) sources on senior dogs’ haircoat and activity. Dogs (mean age 9.16 yr) were fed a control diet (inorganic TM) for 14 d before being assigned to one of three treatments for 3 mo. Treatments included inorganic (Control; n = 10), amino acid-complexed (TMC; n = 17; ZINPRO® ZnMet + Zinpro® Availa® Mins) or lysine and glutamic acid-complexed (TMC-LG; n = 16; Zinpro® ProPath®) supplemental TM. Treatments were formulated to provide standard (Control—100 ppm Zn, 5 ppm Mn, 12 ppm Cu, 45 ppm Fe) or product-recommended (TMC and TMC-LG—100 ppm Zn, 25 ppm Mn, 7 ppm Cu, 45 ppm Fe) TM levels (DM basis). Hair length, regrowth, and shedding were measured along with activity. Dogs fed TMC (26.43 mm; 11.64 mm/mo) and TMC-LG (27.87 mm; 12.6 mm/mo) had significantly (p ≤ 0.05) longer hair that grew faster compared to the Control (18.93 mm; 9.14 mm/mo). At 3 mo TMC-LG-fed dogs had 0.38 g less shed hair, and TMC-fed dogs had 0.87 h more active time/d compared to the Control (p ≤ 0.05). Dogs fed TMC and TMC-LG had superior haircoat characteristics and activity compared to the Control.
Review of the AI-Based Analysis of Abdominal Organs from Routine CT Scans
Authors: Tavakolian Niloofar , Nazemi Azadeh , Suen Ching Yee
Published: February 2025

Accurate and timely segmentation of liver trauma in computed tomography (CT) images is essential for effective diagnosis and management in emergency medicine. This review examines advancements in liver segmentation techniques from 1993 to 2024, focusing on deep learning models and their impact on improving diagnostic accuracy for liver injuries. Early methods relied on basic image processing, which faced limitations due to noise, intensity variations, and complex abdominal anatomy. The advent of deep learning has transformed this domain, with architectures such as UNet, UNet++, UNet3+, multiscale large kernel (MSLUNet), and Swin-Unet achieving significant improvements in segmentation precision. Additionally, generative adversarial networks (GANs), including conditional GAN and pixel-to-pixel (Pix2Pix) GAN, have further enhanced image quality and detail, addressing deficiencies in traditional methods. This review provides a comparative analysis of these models, highlighting their strengths and limitations in liver injury segmentation.
Bi-Objective Optimization for Transportation: Generating Near-Optimal Subsets of Pareto Optimal Solutions
Authors: Zhang Hongyu , Ruan Qingfang , Jin Yong , Wang Shuaian
Published: February 2025

Bi-objective optimization seeks to obtain Pareto optimal solutions that balance two trade-off objectives, providing guidance for decision making in various fields, particularly in the field of transportation. The novelty of this study lies in two aspects. On the one hand, considering that Pareto optimal solutions are often numerous, finding the full set of Pareto optimal solutions is often computationally challenging and unnecessary for practical purposes. Therefore, we shift the focus of bi-objective optimization to finding a subset of Pareto optimal solutions whose resulting set of nondominated objective vectors is the same as, or at least a good approximation of, the full set of nondominated objective vectors for the problem. In particular, we elaborate three methods for generating a near-optimal subset of Pareto optimal solutions, including the revised ϵ-constraint method, the improved revised ϵ-constraint method, and the augmented ϵ-constraint method. More importantly, the near-optimality of the Pareto optimal solution subset obtained by these methods is rigorously analyzed and proved from a mathematical point of view. This study helps to offer theoretical support for future studies to find the subset of Pareto optimal solutions, which reduces the unnecessary workload and improves the efficiency of solving bi-objective optimization problems while guaranteeing a pre-specified tolerance level.
GIS-Based Flood Assessment Using Hydraulic Modeling and Open Source Data: An Example of Application
Authors: Copăcean Loredana , Man Eugen Teodor , Cojocariu Luminiţa L. , Popescu Cosmin Alin , Vîlceanu Clara-Beatrice , Beilicci Robert , Creţan Alina , Herbei Mihai Valentin , Cuzic Ovidiu Ştefan , Herban Sorin
Published: February 2025

The study explores the impact of floods, phenomena amplified by climate change and human activities, on the natural and anthropogenic environment, focusing on the analysis of a section of the Cigher River in the Crișul Alb basin in western Romania. The research aims to identify areas vulnerable to flooding under different discharge scenarios, assess the impact on agricultural lands, and propose a reproducible methodology based on the integration of GIS technologies, hydraulic modeling in HEC-RAS, and the use of LiDAR data. The methodology includes hydrological analysis, processing of the Digital Elevation Model (DEM), delineation of geometries, hydraulic simulation for four discharge scenarios (S1–S4), and evaluation of the flood impact on agricultural and non-agricultural lands. Evaluated parameters, such as water velocity and flow section areas, highlighted an increased flood risk under maximum discharge conditions. The results show that scenario S4, with a discharge of 60 m3/s, causes extensive flooding, affecting 871 hectares of land with various uses. The conclusions emphasize the importance of using modern technologies for risk management, protecting vulnerable areas, and reducing economic and ecological losses. The proposed methodology is also applicable to other river basins, representing a useful model for developing sustainable strategies for flood prevention and management.
Label-Guided Data Augmentation for Chinese Named Entity Recognition
Authors: Jiang Miao , Chen Honghui
Published: February 2025

Chinese named entity recognition (NER) is a fundamental natural language processing (NLP) task that involves identifying and categorizing entities in text. It plays a crucial role in applications such as information extraction, machine translation, and question-answering systems, enhancing the efficiency and accuracy of text processing and language understanding. However, existing methods for Chinese NER face challenges due to the disruption of character-level semantics in traditional data augmentation, leading to misaligned entity labels and reduced prediction accuracy. Moreover, the reliance on English-centric fine-grained annotated datasets and the simplistic concatenation of label semantic embeddings with original samples limits their effectiveness, particularly in addressing class imbalances in low-resource scenarios. To address these issues, we propose a novel Chinese NER model, LGDA, which leverages Label-Guided Data Augmentation to mitigate entity label misalignment and sample distribution imbalances. The LGDA model consists of three key components: a data augmentation module, a label semantic fusion module, and an optimized loss function. It operates in two stages: (1) the enhancement of data with a masked entity generation model and (2) the integration of label annotations to refine entity recognition. By employing twin encoders and a cross-attention mechanism, the model fuses sample and label semantics, while the optimized loss function adapts to class imbalances. Extensive experiments on two public datasets, OntoNotes 4.0 (Chinese) and MSRA, demonstrate the effectiveness of LGDA, achieving significant performance improvements over baseline models. Notably, the data augmentation module proves particularly effective in few-shot settings.
Biological Decontamination by Microplasma
Authors: Blajan Marius Gabriel , Ciorita Alexandra , Surducan Emanoil , Surducan Vasile , Shimizu Kazuo
Published: February 2025

Dielectric-barrier-discharge microplasma has various applications such as flow control, surface treatment, air treatment, or biomedical applications. Microplasma was used for the inactivation of Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. Bacterial strains spread on Petri dishes containing Nutrient Agar were treated with microplasma and, after incubation, inhibition zones were observed. By comparison, the experiments carried out with the already-grown bacteria on the Petri dish did not show any inhibitory response. Environmental air was used as discharge gas. The reactive oxygen and nitrogen species mainly carry out the inactivation process. A negative pulse voltage energized the microplasma electrodes. The microplasma treatment was the most potent against S. aureus, followed by E. coli, and P. aeruginosa, which was the least susceptible bacteria from the tested strains. An increase in the inhibitory efficiency was observed with the increase in discharge voltage from −1.5 kV to −1.7 kV. This research proved the efficiency of microplasma in biological decontamination and provides valuable insights of the inactivation of bacteria carried out with a technology that is suitable for easy integration and portability.
Design and Optimization of a Compliant Morphing Trailing Edge for High-Lift Generation
Authors: Ameduri Salvatore , Galasso Bernardino , Noviello Maria Chiara , Dimino Ignazio , Concilio Antonio , Catalano Pietro , D’Aniello Francesco Antonio , Carossa Giovanni Marco , Pinazo Laurent , Derry John , Biju Britney , Shreedharan Shruthi
Published: February 2025

This work focuses on the design and optimization of a morphing-compliant system developed within the project HERWINGT (Clean Aviation) and aimed at generating high lift during take-off and landing. The device was conceived to replace a conventional flap of a regional aircraft and work in synergy with a droop nose and a flow control system. The architecture is based on a compliant layout, specifically selected to obtain a final morphed shape of the trailing edge of the wing efficient for high-lift purposes and adequately smooth even in cruise clean configuration. At first, the requirements at aircraft level were critically examined and then elaborated to produce the specifications of the morphing device. A layout was then sketched, considering on its potential in approaching the target morphed shape and on its intrinsic criticalities. Starting from this scheme, a simplified FE model was introduced. The scope was to have an efficient predictive tool suited for optimization processes. After having identified the most relevant design parameters (skin thickness distribution, topology of the structure, and actuator interface parameters), the cost function, and the constraints of the problem (structural integrity and stability), a genetic optimization was implemented. Repeating the genetic process starting from different initial populations, some optimized configurations were identified. A trade-off was thus organized on different criteria, such as the lightness of the structure, the load-bearing capability, the force, and the stroke needed by the actuator. The best compromise was finally taken as baseline for the realization of an advanced FE model used to validate the numerical outcomes obtained during the optimization process and as starting point for the next steps planned in the project. The achieved design is characterized by an enhanced aerodynamic performance with the absence of steps and gaps and external track fairings, reduced weight of both the structure and the actuator, reduced maintenance costs due to a simple layout, and smaller take-off and landing distances owing to the high-lift capability and the intrinsic lightness.
Investigation of the Relationship Between the Anti-Oxidant Effect, Brand Trust, Healthiness, and Intention to Purchase Propolis Products: The Moderating Effect of Nutritional Disclosure
Authors: Kim Min Gyung , Kim Ye Kang , Moon Joonho
Published: February 2025

Propolis market is growing, and such growth suggests the importance of understanding consumer behavior. Hence, the aim of this research is to explore the relationship between the anti-oxidant effect, brand trust, healthiness, and consumers’ intention to purchase propolis products. A secondary objective is to examine the moderating role of nutrition disclosure. Survey participants were recruited via the Clickworker platform, yielding 305 valid observations for statistical analysis. The Hayes Process Macro Model 7 was employed to test the research hypotheses. The results indicated that the anti-oxidant effect is positively associated with both healthiness and intention to purchase. Moreover, the findings showed that brand trust is positively related to healthiness and intention to purchase. Additionally, the results disclosed the significant moderating effect of nutrition disclosure on the impact of the anti-oxidant effect and brand trust on healthiness based on the heuristic effect as theoretical underpinning. This research sheds light on the literature by clarifying the relationship between five attributes in the domain of propolis products.
Growth and Rhamnolipid Production Performance of Pseudomonas aeruginosa on Crude Biomass Carbohydrates and Bioenhancer-Based Growth Media
Authors: Sharma Rajat , Lamsal Buddhi P.
Published: February 2025

Novel growth media formulations for improved rhamnolipid production from Pseudomonas aeruginosa PAO1 were evaluated on four carbohydrate sources: glucose, glycerol, soy hull hydrolysate (SHH), and mimicking soy hull hydrolysate (MSH) along with bioenhancers and other media components. This study is aimed at understanding the effect of different types of human neuroendocrine bioenhancers on growth performance and rhamnolipid titer generation of the Pseudomonas aeruginosa PAO1 in a growth media containing sustainable crude biomass carbohydrates. Optimization of the media factors for improved rhamnolipid titers with Pseudomonas aeruginosa PAO1 was performed through a high-throughput response surface study for the best growth rate for concentrations of carbohydrates; bioenhancers, norepinephrine (NE) and dopamine (DP); and iron (Fe). In the high-throughput study, the microbial growth rates for all sugar types ranged between 0.2 and 0.5 log numbers in OD (optical density, indicating the concentration of bacterial cells within a liquid culture, as determined by a spectrophotometer) h−1 at 600 nm, with glucose providing the highest growth rate in the best response surface media combination at 2.5% glucose concentration, 160 µM norepinephrine, 66 µM dopamine, 0.03% Fe concentration. The effect of this media on growth and rhamnolipid production was further verified in 100 mL shake flasks. The highest OD and rhamnolipid titers were achieved for glucose- and glycerol-based media at 2.78 g/L and 2.72 g/L, respectively, whereas significantly lower titers at 1.98 g/L and 1.72 g/L were observed for SHH- and MSH-based media, respectively. No significant growth enhancement effects by the bioenhancers norepinephrine and dopamine were observed at the concentrations evaluated.
New Insights into Earthquake Light: Rayleigh Scattering as the Source of Blue Hue and a Novel Co-Seismic Cloud Phenomenon
Authors: Whitehead Neil Evan , Ulusoy Ulku
Published: February 2025

The New Zealand Kaikoura Earthquake (Mw 7.8, 14 November 2016) produced co-seismic flashes of earthquake light near the ground at midnight, 230 km north of the epicentre. Mostly, there was a white hemisphere in the atmosphere just above the ground, up to 250 m radius, the colour becoming radially increasingly dark blue. Fifteen videos were available for analysis which led to the following new or reaffirmed conclusions: (i) the blue colour is due to Rayleigh Scattering (new explanation); (ii) the light also sometimes occurs within low clouds but not as lightning—this is a new classification of earthquake light; (iii) the lithology may be greywacke, broadening previous literature emphasis on igneous sources; (iv) the light is most probably explained in our study area by seismically pressured microscopic quartz producing electric fields emerging into the atmosphere and reacting with it—mechanisms relying on particle-grinding or creation of cracks in rock are unlikely in the study area; (v) within the Wellington study area, the light is mostly independent of faults or their movement and is caused by seismic impulses which have travelled hundreds of kilometres from the epicentre—this possible independence from faults has not been clearly emphasised previously; and (vi) electrical grid problems are not the explanation.
Optimization and Construction of Jinan Regional Tm Model Based on LSTM and Analysis of Its Influence on the Accuracy of GNSS Inversion PWV
Authors: Wang Shukai , Guo Qiuying , Hua Guihong , Sun Yingjun , Sang Wengang , Wang Zhengyu
Published: February 2025

Water vapor constitutes a vital component of atmospheric precipitation, serving as the fundamental material basis for weather phenomena such as rainfall, and is a significant factor contributing to extreme weather events. The Weighted Mean Temperature (Tm) is a crucial factor in the calculation of Precipitable Water Vapor (PWV) in the atmosphere, directly impacting the quality of GNSS-PWV inversion. The TmN, TmL1, and TmL2 models were constructed through regression analysis and LSTM based on data from the Zhangqiu Radiosonde Station in the Jinan region from 2020 to 2022, as well as ERA5 data. The six Tm models (TmN, TmL1, TmL2, Bevis, GTm, and GPT3) were analyzed by comparing them with the Tm value from the Radiosonde station in 2023. Compared with the Bevis, GTm, and GPT3 models, the accuracy of TmN was improved by 24%, 19%, and 45%, TmL1 was improved by 20%, 16%, and 42%, and TmL2 was increased by 34%, 29%, and 52%. The influence of the above six Tm models on GNSS-PWV accuracy was analyzed using both theoretical and experimental methods. It was demonstrated that the impact of TmL1 and TmL2 on the accuracy of the PWV solution is significantly enhanced in comparison with the other Tm models. The TmL1 and TmL2 models developed in this study offer enhanced accuracy for Tm data utilized in GNSS PWV inversion within the Jinan region.
Retrieval of Atmospheric XCH4 via XGBoost Method Based on TROPOMI Satellite Data
Authors: Zhang Wenhao , Li Yao , Li Bo , Li Tong , Wang Zhengyong , Yang Xiufeng , Jin Yongtao , Zhang Lili
Published: February 2025

Accurate retrieval of column-averaged dry-air mole fraction of methane (XCH4) in the atmosphere is important for greenhouse gas emission management. Traditional XCH4 retrieval methods are complex, while machine learning can be used to model nonlinear relationships by analyzing large datasets, providing an efficient alternative. This study proposes an XGBoost algorithm-based retrieval method to improve the efficiency of atmospheric XCH4 retrieval. First, the key wavelengths affecting XCH4 retrieval were determined using a radiative transfer model. The TROPOspheric Monitoring Instrument (TROPOMI) L1B satellite data, L2 XCH4 products, and auxiliary data were matched to construct the dataset. The dataset constructed was used to train the XGBoost model and obtain the TRO_XGB_XCH4 model. Finally, the accuracy of the proposed model was evaluated using various parameter values and validated against XCH4 products and Total Carbon Column Observing Network (TCCON) ground-based observations. The results showed that the proposed TRO_XGB_XCH4 model had a tenfold cross-validation accuracy R of 0.978, a ground-based validation R of 0.749, and a temporal extension accuracy R of 0.863. Therefore, the accuracy of the TRO_XGB_XCH4 retrieval model is comparable to that of the official TROPOMI L2 product.
Exploring Predictive Modeling for Food Quality Enhancement: A Case Study on Wine
Authors: Yavas Cemil , Kim Jongyeop , Chen Lei , Kadlec Christopher , Ji Yiming
Published: February 2025

What makes a wine exceptional enough to score a perfect 10 from experts? This study explores a data-driven approach to identify the ideal physicochemical composition for wines that could achieve this highest possible rating. Using a dataset of 11 measurable attributes, including alcohol, sulfates, residual sugar, density, and citric acid, for wines rated up to a maximum quality score of 8 by expert tasters, we sought to predict compositions that might enhance wine quality beyond current observations. Our methodology applies a second-degree polynomial ridge regression model, optimized through an exhaustive evaluation of feature combinations. Furthermore, we propose a specific chemical and physical composition of wine that our model predicts could achieve a quality score of 10 from experts. While further validation with winemakers and industry experts is necessary, this study aims to contribute a practical tool for guiding quality exploration and advancing predictive modeling applications in food and beverage sciences.
QRNet: A Quaternion-Based Retinex Framework for Enhanced Wireless Capsule Endoscopy Image Quality
Authors: Frants Vladimir , Agaian Sos
Published: February 2025

Wireless capsule endoscopy (WCE) offers a non-invasive diagnostic alternative for the gastrointestinal tract using a battery-powered capsule. Despite advantages, WCE encounters issues with video quality and diagnostic accuracy, often resulting in missing rates of 1–20%. These challenges stem from weak texture characteristics due to non-Lambertian tissue reflections, uneven illumination, and the necessity of color fidelity. Traditional Retinex-based methods used for image enhancement are suboptimal for endoscopy, as they frequently compromise anatomical detail while distorting color. To address these limitations, we introduce QRNet, a novel quaternion-based Retinex framework. QRNet performs image decomposition into reflectance and illumination components within hypercomplex space, maintaining inter-channel relationships that preserve color fidelity. A quaternion wavelet attention mechanism refines essential features while suppressing noise, balancing enhancement and fidelity through an innovative loss function. Experiments on Kvasir-Capsule and Red Lesion Endoscopy datasets demonstrate notable improvements in metrics such as PSNR (+2.3 dB), SSIM (+0.089), and LPIPS (−0.126). Moreover, lesion segmentation accuracy increases by up to 5%, indicating the framework’s potential for improving early-stage lesion detection. Ablation studies highlight the quaternion representation’s pivotal role in maintaining color consistency, confirming the promise of this advanced approach for clinical settings.
The Complex Relationship Between Sleep Quality and Job Satisfaction: A Machine Learning-Based Bayesian Rule Set Algorithm
Authors: Liu Xin , Qin Nan , Wei Xiaochong
Published: February 2025

In today’s highly competitive and rapidly evolving work environment, employee job satisfaction is a crucial indicator of organizational success and employee well-being. Utilizing the Bayesian rule set (BRS) algorithm, this study systematically explored how multiple variables, such as sleep quality, autonomy, and working hours, interact to influence job satisfaction. Based on an analysis of 618 data points from the CGSS database, we found that a single variable alone is insufficient to significantly improve job satisfaction: instead, a combination of multiple factors can substantially enhance it. Specifically, individuals who are older, have medium to high levels of sleep quality, and work fewer hours report higher job satisfaction. Similarly, individuals with medium to high health levels, high autonomy, and shorter working hours also exhibit high job satisfaction. By employing a multivariable combination analysis approach, this study reveals the complex pathways that affect job satisfaction, providing new theoretical insights and practical guidance for organizations seeking to improve employee satisfaction.
Practical Project Governance Approaches to Achieving Inter-Organization Collaboration Between Stakeholders in Off-Site Construction Projects: Adaptive Dynamic Perspective
Authors: Xue Xiaoyan , Xue Hong
Published: February 2025

As an essential domain of project management, inter-organization collaboration (IOC) is crucial for stakeholders in off-site construction (OSC) projects because of the high linkage between design, production, and site construction stages. Current studies focus on the static relationships between project governance approaches and the OSC project stakeholder collaboration. This study proposes the OSC project stakeholder’s IOC activity as an adaptive system to explore the practical project governance mechanisms to achieve IOC from a dynamics perspective using a survey and Belousov–Zhabotinsky reaction simulation experiment. The finding suggests that project organizational structure and project governance mechanisms are complementary rather than substitutive for improving inter-organizational collaboration between the OSC project stakeholders. The impact paths are practical between project organizational structures and IOC via mediating roles of contract and trust. Moreover, project organizational structure, contract, and trust are a dynamic combination instead of independent. Our study deepens our understanding of the OSC project stakeholders’ IOC by exploring its emergence mechanism, enriching project stakeholder management research on inter-organizational behavioral foundations of collaboration emergence in a temporary projected organization. It also provides practical project governance tools to improve a temporary projected IOC by coordinating project governance mechanisms and project organizational structures.
Modular Construction in the Digital Age: A Systematic Review on Smart and Sustainable Innovations
Authors: Parracho Diogo F. R. , Nour El-Din Mohamed , Esmaeili Iraj , Freitas Sara S. , Rodrigues Leonardo , Poças Martins João , Corvacho Helena , Delgado João M. P. Q. , Guimarães Ana Sofia
Published: February 2025

Modular construction provides numerous benefits over traditional methods, especially when combined with digital technologies, offering a faster, safer, leaner, and more sustainable construction environment. This literature review follows the PRISMA method to assess recent advancements in digital-oriented modular construction towards a sustainable and climate-neutral built environment, identifying research trends and gaps based on three pillars: digital tools, building solutions, and environmental sustainability. This review examines the integration of digital technologies with modular construction methods, extending the analysis to circular and bioclimatic efforts, renewable energy sources, and passive building design strategies. While most articles focus on BIM uses, there is an increasing emphasis on IoT applications that leverage real-time data to achieve sustainability goals. However, no full-scale automated Digital Twin was found in this context. Additionally, Building Energy Modelling (BEM) and Life Cycle Assessment (LCA) tools are frequently discussed, reflecting the push for climate-friendly housing. Despite the interest in parametric and generative design, the integration of machine learning and artificial intelligence applications for sustainable modular construction strategies remains underexplored. Only a few papers acknowledged reaching nZEB requirements despite the great emphasis on passive building solutions and renewable energy sources that contribute to this goal. However, material circularity has yet to achieve its full potential for sustainable modular construction. Moreover, there is some interest in off-grid modular buildings, although further research should be undertaken to analyse the modular construction feasibility for sustainable off-grid communities. Furthermore, the findings highlight the potential of digitalisation in modular construction to enhance efficiency and ensure environmental sustainability within the Architecture, Engineering, and Construction (AEC) sector.
Thermal Comfort and Adaptive Occupant Behaviour in Open Plan Offices in India and Lithuania
Authors: Tuniki Himanshu Patel , Jurelionis Andrius , Rupp Ricardo Forgiarini , Valančius Rokas , Bekö Gabriel
Published: February 2025

Understanding the relationship between thermal comfort and adaptive behaviour in office environments is important for designing sustainable and occupant-centric buildings. This study investigates the thermal sensation, comfort preferences, and adaptive behaviours of occupants in five Indian and two Lithuanian offices. Indoor environmental parameters were measured, and online thermal comfort surveys were carried out. In total, 274 responses were collected. Differences between the two countries were observed in perception of the indoor thermal environment, comfort preferences, and adaptive behaviours. In the Indian offices, despite experiencing higher temperatures and relative humidity, most occupants reported feeling thermally neutral or slightly cool. In the Lithuanian offices (measured in the heating season), a third of the occupants felt slightly cool and another third slightly warm. Occupants in the Indian offices (limited direct access to temperature control, greater prevalence of business attire) showed a higher preference for adjusting the temperature. The occupants in the Lithuanian offices (access to temperature control, more flexible attire) preferred more frequently to adjust their clothing. Consumption of warm or cold beverages for thermal adaptation was equally preferred in the two countries. About 86% of the occupants who did not choose any adaptations reported being comfortable, compared to 65% of those who did. These findings highlight the associations between adaptive behaviour and thermal comfort, emphasising the need to consider individual preferences, environmental factors, and cultural norms in designing comfortable indoor environments.
Optimization and Characterization of Mechanical Properties in Straw-Reinforced Cementitious Composites
Authors: Liu Baohua , Han Dongping , Zhang Fan , Zhang Junqi , Fang Liang
Published: February 2025

This study aimed to reduce the environmental impact of rapeseed straw accumulation and explore its engineering potential by examining how straw affects the mechanical properties of cement–sand composites. Experiments were conducted using varying straw dosages and curing ages to assess water consumption, setting time, flexural and compressive strengths, pore characteristics (via mercury intrusion), hydration products, and microstructures (via thermogravimetry and X-ray diffraction). Results showed that flexural and compressive strengths decreased with higher straw content, most notably up to 2%, but increased with age due to straw’s water absorption, which altered cement hydration and porosity. Over time, enhanced hydration and pore filling improved strength. This research supports straw’s use in civil engineering and advances eco-friendly concrete material development.
The Application of Genetic Algorithm in Seismic Performance Optimization of a Y-Eccentrically Braced Composite Frame
Authors: Zhang Wenxuan , Zhao Yongfei , Wu Zhenhao , Zhao Jizhi , Wang Shuke
Published: February 2025

In this research, the seismic performance optimization of a Y-eccentrically braced composite frame (Y-EBCF) was conducted. An efficient fiber beam–spring element model, which considers the spatial composite effect of the RC slab, was proposed and used to simulate the research objects. A genetic algorithm (GA) was developed for the Y-EBCF, and the chromosome coding method, fitness function, termination condition, and the selection, crossover, and mutation operators were specified. This algorithm was then applied to the optimization problems of arrangement strategies of the eccentric braces and mechanical parameters of shear links for a typical 10-storey composite frame building under different acceleration excitations. The results indicated that, compared to the traditional enumeration algorithm, the proposed GA could find the optimal solution rapidly for the seismic performance optimization problems of the Y-EBCF. The computation cost of the GA for the optimization problems involving the arrangement strategies of the eccentric braces and mechanical parameters of shear links was only 1.5% and 2.6% of those of the enumeration algorithm, respectively. A subsequent parametric analysis revealed that the calculation cost of the GA could be further reduced by adjusting the values of population size, selection, and mutation ratio.
AI and Polyp Detection During Colonoscopy
Authors: Spadaccini Marco , Menini Maddalena , Massimi Davide , Rizkala Tommy , De Sire Roberto , Alfarone Ludovico , Capogreco Antonio , Colombo Matteo , Maselli Roberta , Fugazza Alessandro , Brandaleone Luca , Di Martino Antonio , Ramai Daryl , Repici Alessandro , Hassan Cesare
Published: February 2025

Colorectal cancer (CRC) prevention depends on effective colonoscopy; yet variability in adenoma detection rates (ADRs) and missed lesions remain significant hurdles. Artificial intelligence-powered computer-aided detection (CADe) systems offer promising advancements in enhancing polyp detection. This review examines the role of CADe in improving ADR and reducing adenoma miss rates (AMRs) while addressing its broader clinical implications. CADe has demonstrated consistent improvements in ADRs and AMRs; largely by detecting diminutive polyps, but shows limited efficacy in identifying advanced adenomas or sessile serrated lesions. Challenges such as operator deskilling and the need for enhanced algorithms persist. Combining CADe with adjunctive techniques has shown potential for further optimizing performance. While CADe has standardized detection quality; its long-term impact on CRC incidence and mortality remains inconclusive. Future research should focus on refining CADe technology and assessing its effectiveness in reducing the global burden of CRC.
NINJ1 in Cell Death and Ferroptosis: Implications for Tumor Invasion and Metastasis
Authors: Chen Ssu-Yu , Shyu Ing-Luen , Chi Jen-Tsan
Published: February 2025

NINJ1 was initially recognized for its role in nerve regeneration and cellular adhesion. Subsequent studies have uncovered its participation in cancer progression, where NINJ1 regulates critical steps in tumor metastasis, such as cell migration and invasion. More recently, NINJ1 has emerged as a multifunctional protein mediating plasma membrane rupture (PMR) in several lytic cell death processes, including apoptosis, necroptosis, and pyroptosis. However, its role in ferroptosis—an iron-dependent form of lytic cell death characterized by lipid peroxidation—remained unclear until 2024. Ferroptosis is a tumor suppression mechanism that may be particularly relevant to detached and metastatic cancer cells. This review explores the role of NINJ1 in tumor invasion and metastasis, focusing on its regulation of ferroptosis via a non-canonical mechanism distinct from other cell deaths. We discuss the process of ferroptosis and its implications for cancer invasion and metastasis. Furthermore, we review recent studies highlighting the diverse roles of NINJ1 in ferroptosis regulation, including its canonical function in PMR and its non-canonical function of modulating intracellular levels of glutathione (GSH) and coenzyme A (CoA) via interaction with xCT anti-porter. Given that ferroptosis has been associated with tumor suppression, metastasis, the elimination of treatment-resistant cancer cells, and tumor dormancy, NINJ1′s modulation of ferroptosis presents a promising therapeutic target for inhibiting metastasis. Understanding the dual role of NINJ1 in promoting or restraining ferroptosis depending on cellular context could open avenues for novel anti-cancer strategies to enhance ferroptotic vulnerability in metastatic tumors.
KIF11 and KIF14 Are a Novel Potential Prognostic Biomarker in Patients with Endometrioid Carcinoma
Authors: Antosik Paulina , Durślewicz Justyna , Smolińska-Świtała Marta , Podemski Jonasz , Podemska Edyta , Neska-Długosz Izabela , Jóźwicki Jakub , Grzanka Dariusz
Published: February 2025

Background The current study aimed to evaluate the function of KIF11 and KIF14 in endometroid cancer and assess their role as a prognostic biomarker and therapeutic target for treating endometroid cancer. Methods Therefore, we immunohistochemically tested KIF11 and KIF14 proteins in tumoral and non-tumoral tissue sections from n = 92 endometroid cancer patients with respect to major prognostic and predictive characteristics, as well as treatment outcome. Results We found that KIF11 protein levels were higher in tumor tissues as compared to normal tissues, whereas KIF14 protein levels were lower in cancer tissue. High KIF11 protein levels and low KIF14 protein levels were independent prognostic factors for poor OS. Furthermore, the expression profile of KIF11highKIF14low was associated with the worst OS, and it was superior to each single protein alone in predicting patient prognosis. Conclusions In summary, individual and combined expression of KIF11 and KIF14 proteins may serve as potential prognostic biomarkers for endometroid cancer.
Correction: Kotelevets, L.; Chastre, E. Extracellular Vesicles in Colorectal Cancer: From Tumor Growth and Metastasis to Biomarkers and Nanomedications. Cancers 2023, 15, 1107
Authors: Kotelevets Larissa , Chastre Eric
Published: February 2025

References [...]
Infant and Family Outcomes and Experiences Related to Family-Centered Care Interventions in the NICU: A Systematic Review
Authors: Hodgson Christine R. , Mehra Renee , Franck Linda S.
Published: February 2025

Background/Objectives: Family-centered care (FCC) has been promoted as a model of care in neonatal intensive care units (NICU) for decades. We aimed to synthesize recent evidence about infant and parent outcomes and experiences of FCC interventions in the NICU. Methods: Studies were identified through searches of PubMed, CINAHL, Embase, PsycInfo, and Web of Science (2019–2024). We systematically reviewed English language research from peer-reviewed journals. We excluded studies about Family-Integrated Care and Close Collaboration with Parents to avoid redundancy with other recent reviews. Results: Twenty studies evaluated 19 FCC interventions compared with regular NICU care for a total of 3502 parents/primary caregivers of infants in NICUs in 11 countries. The designs were quantitative (n = 16), qualitative (n = 3), and mixed methods (n = 1). Significant improvements in infant outcomes included feeding (n = 3), weight (n = 1), and length of stay (n = 1). There were no worsened infant outcomes. Significant improvements in parent outcomes included participation, experience, satisfaction, and parent mental health. Two studies had mixed results for parent outcomes, with minimal worsened outcomes. Qualitative findings were also mostly positive. Conclusions: Recent research shows positive infant and family outcomes with a range of FCC interventions in the NICU. However, more RCTs comparing interventions and using similar validated outcome measures are needed.