bluuebunny/crossref_metadata_2025 huggingface dataset:
Framework for Apple Phenotype Feature Extraction Using Instance Segmentation and Edge Attention Mechanism
Authors: Wang Zichong , Cui Weiyuan , Huang Chenjia , Zhou Yuhao , Zhao Zihan , Yue Yuchen , Dong Xinrui , Lv Chunli
Published: January 2025

A method for apple phenotypic feature extraction and growth anomaly identification based on deep learning and natural language processing technologies is proposed in this paper, aiming to enhance the accuracy of apple quality detection and anomaly prediction in agricultural production. This method integrates instance segmentation, edge perception mechanisms, attention mechanisms, and multimodal data fusion to accurately extract an apple’s phenotypic features, such as its shape, color, and surface condition, while identifying potential anomalies which may arise during the growth process. Specifically, the edge transformer segmentation network is employed to combine deep convolutional networks (CNNs) with the Transformer architecture, enhancing feature extraction and modeling long-range dependencies across different regions of an image. The edge perception mechanism improves segmentation accuracy by focusing on the boundary regions of the apple, particularly in the case of complex shapes or surface damage. Additionally, the natural language processing (NLP) module analyzes agricultural domain knowledge, such as planting records and meteorological data, providing insights into potential causes of growth anomalies and enabling more accurate predictions. The experimental results demonstrate that the proposed method significantly outperformed traditional models across multiple metrics. Specifically, in the apple phenotypic feature extraction task, the model achieved exceptional performance, with accuracy of 0.95, recall of 0.91, precision of 0.93, and mean intersection over union (mIoU) of 0.92. Furthermore, in the growth anomaly identification task, the model also performed excellently, with a precision of 0.93, recall of 0.90, accuracy of 0.91, and mIoU of 0.89, further validating its efficiency and robustness in handling complex growth anomaly scenarios. The method’s integration of image data with agricultural knowledge provides a comprehensive approach to both apple quality detection and growth anomaly prediction, offering reliable decision support for agricultural production. The proposed method, by integrating image data with agricultural domain knowledge, provides precise decision support for agricultural production, not only improving the efficiency and accuracy of apple quality detection but also offering reliable technical assurance for agricultural economic analysis.
Unmanned-Aerial-Vehicle-Based Multispectral Monitoring of Nitrogen Content in Canopy Leaves of Processed Tomatoes
Authors: Zhang Hao , Zhang Li , Wu Hongqi , Wang Dejun , Ma Xin , Shao Yuqing , Jiang Mingjun , Chen Xinyu
Published: January 2025

Nitrogen serves as a critical nutrient influencing the yield and quality of processed tomatoes; however, traditional methods for assessing its levels are both labor-intensive and costly. This study aimed to explore an efficient monitoring approach by analyzing the relationship between leaf nitrogen content (LNC) and canopy spectral reflectance characteristics throughout the growth stages of processed tomatoes at the Laolong River Tomato Base in Changji City, Xinjiang. The experimental design incorporated nine treatments, each with three replicates. LNC data were obtained using a dedicated leaf nitrogen content analyzer, while drones were utilized to capture multispectral images for the extraction of vegetation indices. Through Pearson correlation analysis, the optimal spectral variables were identified, and the relationships between LNC and spectral variables were established using models based on backpropagation (BP), multiple linear regression (MLR), and random forests (RFs). The findings revealed that the manually measured LNC data exhibited two peak values, which occurred during the onset of flowering and fruit setting stages, displaying a bimodal pattern. Among the twelve selected vegetation indices, ten demonstrated spectral sensitivity, passing the highly significant 0.01 threshold, with the Normalized Difference Chlorophyll Index (NDCI) showing the highest correlation during the full bloom stage. The combination of the NDCI and RF model achieved a prediction accuracy exceeding 0.8 during the full bloom stage; similarly, models incorporating multiple vegetation indices, such as RF, MLR, and BP, also reached prediction accuracies exceeding 0.8. Consequently, during the seedling establishment and initial flowering stages (vegetation coverage of <60%), the RF model with multiple vegetation indices was suitable for monitoring LNC; during the full bloom stage (vegetation coverage of 60–80%), both the RF model with the NDCI and the MLR model with multiple indices proved effective; and during the fruit setting and maturation stages (vegetation coverage of >80%), the BP model was more appropriate. This research provides a scientific basis for the cultivation management of processed tomatoes and the optimization of nitrogen fertilization within precision agriculture. It advances the application of precision agriculture technologies, contributing to improved agricultural efficiency and resource utilization.
Optimizing Cassava Growth with Localized Struvite Application: Root Proliferation and Fertilization Efficiency
Authors: Borges Roger , Giroto Amanda S. , Ohrem Benedict , Beckmann Silas , Ademi Ali , Boeckem Vera , Bochmann Helena , Müller-Linow Mark , Lenz Henning , Ribeiro Caue , Wojciechowski Tobias , Jablonowski Nicolai D. , Postma Johannes A.
Published: January 2025

Cassava is a root storage crop that is important to the starch industry and food security. In this study, the sustainable fertilization of cassava using local placement of struvite, a fertilizer recovered from wastewater, rich in nitrogen, phosphorus, and magnesium, was investigated. It was asked if struvite is a suitable fertilizer for cassava, if it is likely to spread through the substrate (leach), and if roots can proliferate and utilize a concentrated placement of struvite. Cassava was grown in rhizoboxes under different fertilizer placement strategies: unfertilized control, homogeneous fertilizer distribution in the top 20 cm (‘homogenized’), a strip placement (‘layer’) at 20 cm depth, and a localized ‘depot’ at the same depth. Shoot and root growth responses were monitored over 8 weeks. Cassava growth was significantly improved with struvite fertilization. The fertilizer remained localized, with minimcnal spread during the 8 weeks of experimentation. Both the ‘layer’ and ‘homogenized’ struvite placements resulted in comparable biomass production, significantly greater than the unfertilized treatment. Plants in the ‘depot’ placement initially grew similar to the unfertilized treatment as roots took time to locate and proliferate into the fertilizer depot. Afterward, plants in the ‘depot’ treatment grew quickly, resulting in an intermediate biomass at harvest. Notably, cassava exhibited strong root proliferation in response to concentrated struvite, which did not compromise deep rooting but instead appeared to enhance it, increasing specific root length. These findings suggest that strip fertilization with struvite may offer a sustainable fertilization strategy for cassava, warranting further investigation in field trials.
Modelling the Spread of Foot and Mouth Disease in Different Livestock Settings in Italy to Assess the Cost Effectiveness of Potential Control Strategies
Authors: Pesciaroli Michele , Bellato Alessandro , Scaburri Alessandra , Santi Annalisa , Mannelli Alessandro , Bellini Silvia
Published: January 2025

Foot and Mouth disease (FMD) transmission is strongly related to the distribution and density of FMD-susceptible animals. In this study, we applied a model to simulate the spread of FMD in three Italian regions with different livestock demographics (densely, medium, and sparsely populated) in order to assess the cost effectiveness of the disease control options within the framework of the Italian contingency plan. The results of the simulations showed that stamping-out was sufficient to control the outbreak in the sparsely and medium populated areas whereas, in densely populated areas, only vaccinations could effectively control an outbreak. We also estimated the economic resources needed for the adoption of different control strategies, considering livestock indemnity, cleaning, disinfection and disposal, surveillance, vaccination and personnel costs. The results obtained showed that indemnity due to culling had the highest impact on the costs in all scenarios and vaccination resulted in the most cost-effective option to apply in densely populated livestock areas. The results of this study can be a useful aid to Competent Authorities in the preparation of contingency plans against FMD.
The Role of Paraoxonase-1 Activity, Apolipoprotein B Levels, and Apolipoprotein B/Apolipoprotein A-I Ratio as Risk Markers for Aortic Stenosis in Patients with a Bicuspid Aortic Valve
Authors: Kwiatkowska Maria , Mickiewicz Agnieszka , Krzesińska Aleksandra , Kuchta Agnieszka , Jankowski Maciej , Gruchała Marcin , Fijałkowski Marcin
Published: January 2025

The bicuspid aortic valve (BAV) is commonly associated with the early degeneration of the aortic valve. Up to 45% of BAV patients over the age of 50 develop aortic stenosis (AS). Although published data indicate a robust interplay between lipids and calcific AS in tricuspid aortic valve patients, the studies on the BAV population are lacking. We aimed to evaluate the association between selected lipid markers and the occurrence of AS in BAV patients. Methods: The study included 76 adults (21 female) with a BAV diagnosed by echocardiography, divided by age and AS diagnosis. Biochemical parameters concentrations in serum were measured: high density lipoprotein cholesterol (HDL-C) levels by standard enzymatic colorimetric tests, low density lipoprotein cholesterol (LDL-C) levels by the Friedewald formula, apolipoprotein A-I (Apo AI) and apolipoprotein B (Apo B) serum concentration by the nephelometric method, and paraoxonase-1 activity (PON-1 ASE) and arylesterase activity (PON-1 ARE) based on paraoxon and phenyl acetate hydrolysis. Results: A total of 54 patients (15 female) were more than 45 years old and 22 (6 female) were 45 or less years old. BAV patients with AS aged ≤45 had higher levels of Apo B, compared to those without AS [110.5 (102–132) vs. 95.6 (77–101) mg/d; p 0.044]. Similarly, Apo B/Apo AI ratio was higher in BAV patients with AS aged ≤45, compared to those without AS [(0.8 (0.7–1) vs. 0.6 (0.5–0.7); p 0.029]. In the group aged ≤45, Apo B showed a positive correlation with the aortic valve peak transvalvular velocity (AV Vmax) measurement (R Spearman 0.6, p 0.004). We found also that, among young BAV patients, those with AS had a lower level of PON-1 ARE compared to the cohort without AS [63.4 (52–80) vs. 85.3 (70–102); p 0.012]. We did not find any differences in lipid parameters in patients aged >45. Conclusions The metabolic link between Apo B level and Apo B/AI ratio with AS presence in BAV patients under 45 years of age suggests a significant impact of these parameters on the earlier development of AS in the BAV population. Molecules associated with high density lipoprotein and its antioxidant function, such as PON1, are valuable markers for AS development, compared to HDL-C and LDL-C levels.
Strata Control by Roof Blasting for Bord and Pillar Mining Method in Mechanized Depillaring Panels
Authors: Gautam Abhishek , Kumar Ashok , Ram Sahendra , Skrzypkowski Krzysztof , Zagórski Krzysztof , Zagórska Anna , Madziarz Maciej , Migda Krzysztof
Published: January 2025

This article discusses the challenges and remedial measures (roof blasting) adopted to deal with extremely difficult cavable roofs while working with Continuous Miner Technology (CMT) in Bord and Pillar mining method. The main objective of the roof blasting in the goaf is to induce caving to minimize the abutment load in and around the working face to prevent incidences of coal bumps, goaf swelling, pillar spalling, and air blasts. It was found that roof blasting is subjected to the nature of local roof falls, results of strata monitoring studies, and the hanging span of roof strata near the line of extraction. Efforts have been made to design different geotechnical elements and structures involved during the mechanized depillaring panel of the Tawa-I mine, using empirical methods to minimize the issues of roof overhang in the goaf. Numerical simulation studies were also performed to validate the design predicted by empirical methods. The Cavability Index indicated that the roof at Tawa-I mine is difficult to cave. To address this, roof blasting design strategies have been discussed to promote caving and minimize roof overhang, ensuring safe and efficient strata control while operating CMT in the challenging and complex geo-mining conditions of the mine.
Optimized Enzymatic Extraction of Phenolic Compounds from Verbascum nigrum L.: A Sustainable Approach for Enhanced Extraction of Bioactive Compounds
Authors: Brienza Filippo , Calani Luca , Bresciani Letizia , Mena Pedro , Rapacioli Silvia
Published: January 2025

Verbascum nigrum, commonly known as black mullein, is widely used in traditional medicine for its expectorant, mucolytic, sedative, and diuretic properties. This study aimed to develop and optimize a standardized method for extracting phenolic compounds from V. nigrum using enzymatic pretreatment followed by solvent extraction. Enzymatic treatment does not rely on harmful solvents and is a low energy-intensive process, making it a suitable green technology for the food, cosmetic, and pharmaceutical industries. The research explored the use of different lignocellulolytic enzymes, including pectinase, cellulase, α-amylase, and xylanase, to break down plant cell walls, enhancing the release and bioaccessibility of active compounds. The two-step extraction process proposed combined enzymatic pretreatment and hydroalcoholic extraction, resulting in a considerably improved yield of phenolic compounds (24 mg/g DM). Analytical characterization using a high-performance liquid chromatography (HPLC) system coupled with a diode-array-detector (DAD) and ultra-high-performance liquid chromatography (UHPLC) coupled with DAD and tandem mass spectrometry (MS/MS) revealed a higher concentration of target bioactive compounds in enzymatically treated extracts compared to traditional methods, including phenolic derivatives (e.g., caffeic acid, p-coumaric acid, and verbascoside), and flavonoids (e.g., luteolin). Up to 22 phenolic and flavonoid compounds were characterized. This study provides new insight into the potential of enzymatic extraction as a green and efficient alternative to conventional extraction methods, for the production of high-quality herbal products richer in (poly)phenolic compounds, highlighting its potential for industrial applications.
Optimizing Large Language Models: A Deep Dive into Effective Prompt Engineering Techniques
Authors: Son Minjun , Won Yun-Jae , Lee Sungjin
Published: January 2025

Recent advancements in Natural Language Processing (NLP) technologies have been driven at an unprecedented pace by the development of Large Language Models (LLMs). However, challenges remain, such as generating responses that are misaligned with the intent of the question or producing incorrect answers. This paper analyzes various Prompt Engineering techniques for large-scale language models and identifies methods that can optimize response performance across different datasets without the need for extensive retraining or fine-tuning. In particular, we examine prominent Prompt Engineering techniques including In-Context Learning (ICL), Chain of Thought (CoT), Retrieval-Augmented Generation (RAG), Step-by-Step Reasoning (SSR), and Tree of Thought (ToT), and we apply these techniques to leading LLMs such as Gemma2, LlaMA3, and Mistral. The performance of these models was evaluated using the AI2 Reasoning Challenge (ARC), HellaSwag, Massive Multitask Language Understanding (MMLU), TruthfulQA, Winogrande, and Grade School Math (GSM8k) datasets across metrics such as BLEU, ROUGE, METEOR, BLEURT, and BERTScore. The experimental results indicate that the most suitable Prompt Engineering technique can vary depending on the characteristics of each dataset. Specifically, for datasets emphasizing mathematical and logical reasoning, Prompt Engineering strategies centered around CoT, SSR, and ToT were found to be advantageous. For datasets focusing on natural language understanding, ICL-centric strategies were more effective, while RAG-based strategies were beneficial for datasets where factual accuracy is crucial. However, it was also observed that the optimal combination of Prompt Engineering techniques could differ depending on the specific LLM, indicating that fine-tuning the Prompt Engineering approach to the model and dataset is essential for achieving the best performance. The findings indicate that as LLMs become more advanced, their reliance on Prompt Engineering (PE) techniques diminishes, yet the magnitude of their performance improvement when PE strategies are applied increases. Furthermore, these advanced models tend to depend less on ICL techniques while exhibiting a greater reliance on RAG strategies. It is also evident that implementing RAG with PE-based preprocessing yields superior performance enhancements compared to the mere application of RAG on raw data.
Phytochemical Research and Screening of Pharmacological Activity in Eryngium planum L. Herb Extracts
Authors: Matiusha Ksenia , Grytsyk Andriy , Hrytsyk Roman , Raal Ain , Koshovyi Oleh
Published: January 2025

Species of the genus Eryngium L. of the Apiaceae family are successfully used in folk medicine in various countries worldwide, but they are hardly implemented in official medicinal and pharmaceutical practices. Therefore, it is advisable to conduct phytochemical and pharmacological research in E. planum L. herb extracts to develop and implement new phytomedicines based on this raw material. Purified water, and 40% and 70% ethanol were used for obtaining soft extracts. A total of seven hydroxycinnamic acids, six flavonoids, and three tannin metabolites were identified and quantified in the E. planum extracts by HPLC. These extracts were characterized as practically non-toxic medicines (V toxicity class, LD50 > 5000 mg/kg). The hepatoprotective activity of the E. planum extracts has been established. They were affected to reduce serum thiobarbituric acid (TBA) levels by 29.3%, 31.5%, and 32.4%, respectively, compared to untreated animals and in liver homogenate by 59.5%, 65.4%, and 66.8%, respectively. The alanine transaminase (ALT) activity decreased by 26.9%, 30.8%, and 33.8%, respectively. The aspartate transaminase (AST) activity decreased by 23.9%, 25.7%, and 30.5%, respectively. The sedative activity of E. planum extracts was studied for the first time. The 70% ethanol extract has the most pronounced sedative effect due to a significant decrease in motor activity (by 2.4 times compared to the control group) in the «Open Field test» and reduction in concern in the «Cube tests», «Raised Cross Maze», and “Black and White Camera”. This extract also demonstrates a moderate antibacterial effect against gram-positive microorganisms (8–10 mm), including staphylococci, streptococci, and bacilli. These results provide a foundation for further preclinical and clinical studies of the dry extract of E. planum herb (extractant: 70% ethanol) to integrate it into modern medical practice and develop new supplements.
Sink–Source Characteristics of Carbon and Nitrogen in Four Typical Urban Water Bodies Within a Medium-Sized City of East China
Authors: Xie Shaowen , Yang Shengnan , Deng Yanghui , Xu Haofan , Zhou Yanbo , Liu Shujuan , Zhou Hongyi , Yang Fen , Wei Chaoyang
Published: January 2025

The urban water environment, an integral component of the terrestrial hydrosphere, is closely linked to human activities and serves as a fundamental resource for industrial and agricultural development. Sedimentary organic matter in water bodies contains rich biological, physical, and chemical information, playing a central role in nutrient cycling and serving as a primary reservoir for nutrient accumulation. This study assesses the water quality, chemical indicators, and sediment productivity of four typical urban water bodies (Canal, Pond, Lake, and River) in Shaoxing City, eastern China. The results show that artificial water bodies, particularly canals, have higher dissolved oxygen (DO) compared to natural water bodies. Stationary water bodies, such as lakes and ponds, generally have higher total dissolved solids (TDS) and electrical conductivity (EC) than flowing water bodies like rivers and canals. All four urban water body types slightly exceed China’s Class-V water quality standard for total nitrogen (TN), with canals, lakes, ponds, and rivers averaging 1.29, 1.22, 1.23, and 1.23 times the standard, respectively. Ponds exhibit the highest total dissolved nitrogen (TDN) content, while ammonium (NH4+–N) and nitrate (NO3−–N) levels are relatively consistent across the bodies, except for lower NO3−–N in lakes. Higher organic matter in canals and lakes, indicated by chlorophyll-a (Chl-a) and permanganate index (CODMn), suggests greater eutrophication compared to ponds and rivers. Sediment total organic nitrogen (TON) content is relatively uniform across all water bodies, with slightly higher values in lakes and rivers. Total organic carbon (TOC) content is highest in lake sediments, 1.51 times that of canals. Carbon/nitrogen (C/N) ratios vary, with ponds and lakes showing the highest averages. Source quantification using isotopic analysis (δ13C and δ15N values) indicates that phytoplankton is the primary sedimentary organic matter source in rivers and canals, while terrestrial sources are significant in lakes and ponds. Sewage notably contributes to rivers and canals. These findings highlight the need for targeted pollution control strategies, focusing on phytoplankton and sewage as key sedimentary organic matter sources to mitigate eutrophication and enhance water quality in urban environments.
Development of Deployable Reflector Antenna for the SAR-Satellite, Part 3: Environmental Test of Structural-Thermal Model
Authors: Kim Hyun-Guk , Kim Dong-Geon , Do Ryoon-Ho , Kwak Min-Ju , Koo Kyung-Rae , Yu Youngjoon
Published: January 2025

The concept of synthetic aperture radar (SAR) has the advantage of being able to obtain high-quality images even when the target area is at night or covered with obstacles such as clouds or fog. These imaging capabilities have led to a rapid increase in demand for space SAR imagery across a variety of sectors, including government, military, and commercial sectors. The SAR-based deployable reflector antenna was developed in this series of paper. The satellite performance is influenced by the aperture size of an antenna. To improve the image acquisition performance, the SAR antenna has the configuration of several foldable CFRP reflectors. In this paper, the experimental investigation of the Structural-thermal model deployable reflector antenna is performed. During the launch condition, the satellite and payload are subjected to the dynamic load. In the STM phase, the acoustic test was conducted to evaluate the structural stability of the deployable reflector antenna within the acoustic environment. The sinusoidal vibration test was implemented to investigate the fundamental frequency for inplane/normal directions and evaluate the structural stability of reflector antenna. By using experimental data obtained from the thermal-balance test, the well-correlated thermal analysis model was established to execute the orbital thermal analysis. The experimental results of the environmental test in STM phase show that the deployable reflector antenna has structural stability for the structural/thermal environments. The configuration of the deployable reflector antenna determined in STM phase can be applied to the qualification model.
Regioselective De Novo Synthesis of Phenolic Isoprenoids Grifolin and Neogrifolin
Authors: Lim Boram , Yeo Huisu , Han Seunghyo , Kim Dabin , Lee Hansuk , Koo Sangho
Published: January 2025

The total synthesis of biologically and pharmacologically important phenolic isoprenoids, grifolin and neogrifolin, was developed through simple allylation and cyclization procedures using only ethyl acetoacetate, ethyl crotonate, and farnesyl bromide as substrates. The regioisomeric terpenophenols, which consist solely of orcinol and farnesyl moieties, cannot be synthesized purely by direct coupling between the units. The regioselectivity issue was solved by controlling the timing of the allylation of β-ketoester with farnesyl bromide and the cyclization with ethyl crotonate. 2-Farnesyl-5-methyl-cyclohexane-1,3-dione and 6-farnesyl-5-methyl-cyclohexane-1,3-dione were prepared in a highly regioselective manner from ethyl acetoacetate in overall yields of 43% and 40%, respectively. The oxidative aromatization of the regioisomeric cyclohexane-1,3-diones produced grifolin and neogrifolin, respectively.
Better Cone-Beam CT Artifact Correction via Spatial and Channel Reconstruction Convolution Based on Unsupervised Adversarial Diffusion Models
Authors: Dong Guoya , He Yutong , Liu Xuan , Dai Jingjing , Xie Yaoqin , Liang Xiaokun
Published: January 2025

Cone-Beam Computed Tomography (CBCT) holds significant clinical value in image-guided radiotherapy (IGRT). However, CBCT images of low-density soft tissues are often plagued with artifacts and noise, which can lead to missed diagnoses and misdiagnoses. We propose a new unsupervised CBCT image artifact correction algorithm, named Spatial Convolution Diffusion (ScDiff), based on a conditional diffusion model, which combines the unsupervised learning ability of generative adaptive networks (GAN) with the stable training characteristics of diffusion models. This approach can efficiently and stably achieve CBCT image artifact correction, resulting in clear, realistic CBCT images with complete anatomical structures. The proposed model can effectively improve the image quality of CBCT. The obtained results can reduce artifacts while preserving the anatomical structure of CBCT images. We compared the proposed method with several GAN- and diffusion-based methods. Our method achieved the highest corrected image quality and the best evaluation metrics.
A Case Series Focusing on Blunt Traumatic Diaphragm Injury at a Level 1 Trauma Center
Authors: Sharma Bharti , Kafaru Musili , Agriantonis George , Davis Aden , Bhatia Navin D. , Twelker Kate , Shafaee Zahra , Dave Jasmine , Mestre Juan , Whittington Jennifer
Published: January 2025

Introduction: Detection of blunt traumatic diaphragm injury (TDI) can be challenging in the absence of surgical exploration. Our objective is to study the mechanisms of injury and detection modes for patients with blunt TDI. Methods: This is a single-center, retrospective review conducted in a level 1 trauma center from 2016 to 2023, inclusive. We identified seven patients with blunt TDI using the primary mechanisms and trauma type. Results: Out of seven patients, two were associated with motor vehicle collisions, four were pedestrians struck, and one fell down the stairs. The mean ISS was 48.4 (29–75). Of the seven patients with blunt TDI, four died in the trauma bay–two from traumatic arrest and two died spontaneously. Multiple rib fractures were one of the common injury patterns in six cases, whereas in the remaining case, blunt TDI was confirmed at laparotomy and repaired. One patient died two days after admission. Of the two patients who survived, one had a TDI identified during video-assisted thoracic surgery (VATS) for retained hemothorax, and one patient had a TDI repaired during emergent exploratory laparotomy for other injuries. In the remaining four patients, blunt TDI was confirmed based on their autopsy reports. Conclusions: Injuries in all seven cases were sustained with a high-energy injury mechanism. Multiple rib fractures were reported in six cases. Based on our findings, we recommend that clinicians maintain a high level of suspicion for blunt TDI in patients with thoracoabdominal trauma, especially in cases with rib fractures or high-impact trauma.
Do Early Childhood Educators Benefit from a Playful Working Environment? A Study on Workplace Fun and Work Engagement
Authors: Yang Jialing , Wang Xinghua , Hong Huifang
Published: January 2025

This study investigated early childhood education (ECE) teachers’ workplace fun and its relationship with their psychological capital and work engagement, both of which are crucial elements in improving their work efficiency. The relationship was investigated using quantitative methodology. Hypotheses and conceptual models were tested by structural equation modeling (SEM) on the raw data from 196 full-time ECE teachers via questionnaire surveys that investigated ECE teachers’ experiences of four aspects of workplace fun (i.e., formal fun activities, supportive practices for fun, coworker socializing, and fun job responsibilities). It was revealed that fun job responsibilities positively predicted the work engagement of ECE teachers. Furthermore, supportive practices for fun at ECE centers can indirectly predict the work engagement of teachers via the mediating effect of psychological capital. Based on the findings of this study, suggestions are provided to enhance teachers’ work engagement, including implementing supportive practices for fun by organizational management and promoting enjoyment in teachers’ job responsibilities.
A Study on Guidelines for Constructing Building Digital Twin Data
Authors: Jeong Dawoon , Jeong Taeyun , Lee Changyun , Choi Youngmin , Lee Dohun
Published: January 2025

In South Korea, to systematically share and operate data related to the national level of the digital twin, a reference model standard for the National Digital Twin (NDT) concept was established in 2021. This was followed by the Korean Industrial Standards (KS) for buildings. Despite these efforts, the implementation of digital twin projects faces challenges owing to a low level of understanding of the standards and the absence of a standardized data construction process. Consequently, data construction that adheres to these standards is not being accomplished. Additionally, a lack of understanding of data models, semantic elements, and GML editing methods has led to the creation of appearance-focused data. To address these issues, this study proposes a digital twin data (building domain) construction guide that organizes geometric information, semantic information, and attribute information for building-related digital twin data components. This study aims to enable stakeholders to easily construct fundamental digital twin data in accordance with the standards, ensuring high-quality product creation that meets the requirements. Furthermore, the detailed data construction requirements defined in this guide will allow it to serve as a manual usable by both the public and private sectors. However, the proposed data model currently operates at a conceptual and logical level, which may limit its immediate applicability. Therefore, future research should include expert evaluations of the model and its transformation into a physical model that can be implemented and deployed on the relevant platform.
Experimental Study on Bond Fatigue Between Carbon Fiber-Reinforced Polymer Bars and Seawater–Sea Sand Concrete Under Seawater Immersion and Dry–Wet Cycle Conditions
Authors: Yang Fu , Gan Weiquan , Chen Bingsan , Wu Jiangchuan , Yuan Shiwen
Published: January 2025

The durability of carbon fiber-reinforced polymer (CFRP) bars in marine environments is essential for their application in seawater–sea sand concrete (SWSSC), especially under cyclic loading conditions. While previous studies primarily focused on static bonding performance, the effects of seawater immersion and dry–wet cycles on bond fatigue behavior at CFRP–SWSSC interfaces remain underexplored. This study investigated the bond fatigue performance of CFRP bars and SWSSC under seawater immersion and dry–wet cycling conditions. Eighteen CFRP bar-SWSSC bond specimens were divided into three categories and prepared for static and fatigue pull-out tests. The effects of varying stress levels (fatigue upper load/static bond ultimate load) after seawater immersion and dry–wet cycling on fatigue failure modes, bond–slip behavior, and fatigue characteristics were evaluated. The results show that seawater immersion and dry–wet cycling significantly degrade the performance of bonds between CFRP bars and SWSSC, with an average bond strength reduction of 10.31%. These conditions reduce fatigue cycles and stiffness while increasing bond–slip (relative displacement at the bar–concrete interface) and residual–slip (displacement after unloading). Moreover, dry–wet cycling has a greater negative impact on fatigue bond performance than seawater immersion. Higher fatigue stress levels exacerbate damage and crack propagation at the CFRP–SWSSC interface, leading to significant increases in both bond–slip and residual-slip. Under similar conditions, higher stress levels enhance bond stiffness. However, excessively high stresses may lead to bond fatigue failures. Using experimental data and existing fatigue bond–slip constitutive models, a customized model for CFRP bars in SWSSC was developed. These findings highlight that marine environments and fatigue loading severely impair bond performance, thereby emphasizing the importance of careful design for marine applications. The proposed model offers a reliable framework for predicting bond–slip behavior under fatigue conditions, enhancing the understanding of CFRP–SWSSC interactions and supporting the design of durable marine infrastructure.
Decoding Concrete’s Environmental Impact: A Path Toward Sustainable Construction
Authors: Tran Cuong N. N. , Illankoon I. M. Chethana S. , Tam Vivian W. Y.
Published: January 2025

The construction industry is a major contributor to global greenhouse gas emissions, driven by the extensive use of conventional concrete in building activities. This study evaluates the environmental impacts of various concrete types, including innovative alternatives, using a computational life cycle assessment (LCA) model tailored to the Australian context. Key stages considered include raw material extraction, production, transportation, and end-of-life recycling. Results demonstrate that replacing 40% of cement with supplementary cementitious materials (SCMs) such as fly ash reduces global warming potential (GWP) by up to 25% compared to conventional concrete. Furthermore, carbonation curing technology shows a 15% reduction in CO2 emissions during the production phase, underscoring its potential to significantly enhance sustainability in construction. High-strength concrete poses significant ecological challenges; however, incorporating SCMs such as fly ash, blast-furnace slag, and silica fume effectively mitigates these impacts. Recycling 60% of concrete demolition waste further decreases environmental impacts by over 20%, aligning with circular economy principles and supporting resource recovery. The findings provide actionable insights for engineers, architects, and policymakers, facilitating the design of sustainable concrete solutions that balance structural performance with reduced ecological footprints. Future research should explore dynamic modelling and broader socio-economic factors to refine sustainable practices. This study underscores the critical importance of adopting innovative materials and recycling practices to minimise the environmental impact of construction activities globally.
A TaqMan-Based qRT-PCR Assay for Accurate Evaluation of the Oncogenic TrkAIII Splice Variant in Tumor cDNAs
Authors: Sbaffone Maddalena , Farina Antonietta Rosella , Martelli Ilaria , Pontieri Eugenio , Guadagni Stefano , Mackay Andrew Reay , Cappabianca Lucia , Zelli Veronica
Published: January 2025

Background: Alternative NTRK1/TrkA splicing resulting in TrkAIII expression, originally discovered in advanced-stage metastatic neuroblastomas, is also pronounced in prostate, medullary thyroid, glioblastoma multiforme, MCPyV-positive Merkel cell, cutaneous malignant melanoma, and pituitary neuroendocrine tumor subsets. In tumor models, TrkAIII exhibits actionable oncogenic activity equivalent to the TrkT3-fused oncogene, and in tumor cell lines, alternative TrkAIII splicing is promoted by hypoxia, nutrient deprivation, endoplasmic reticulum stress, and SV40 large T antigen, implicating tumor microenvironmental conditions and oncogenic polyoma viruses in tumor-associated TrkAIII expression. Collectively, these observations characterize TrkAIII as a potentially frequent, actionable oncogenic alternative to TrkA gene fusion in different tumor types. Currently, therapeutic approval for efficacious Trk inhibitors is restricted to Trk-fused gene positive tumors and not for tumors potentially driven by TrkAIII. Methods: With the therapeutically relevant aim of improving the identification of tumors potentially driven by TrkAIII, we have developed a TaqMan-based qRT-PCR assay for evaluating TrkAIII expression in tumor cDNAs. Results: This assay, validated using gel-purified fs-TrkA and TrkAIII cDNAs alone and in complex cDNA mixtures, employs primers and probes designed from fs-TrkA and TrkAIII sequences, with specificity provided by a TaqMan probe spanning the TrkAIII exon 5–8 splice junction. It is highly efficient, reproducible, and specific and can detect as few as 10 TrkAIII copies in complex RNAs extracted from either fresh or FFPE tumor tissues. Conclusions: Inclusion of this assay into precision oncology algorithms, when paired with fs-TrkA qRT-PCR and TrkA immune histochemistry, will make it easier to identify patients with therapy-resistant, advanced-stage metastatic Trk-fused gene-negative tumors potentially driven by TrkAIII, for whom approval of third-line effective Trk inhibitors could be extended.
Comparative Analysis of Early Class III Malocclusion Treatments—A Systematic Review and Meta-Analysis
Authors: Otel Andrei , Montiel-Company José María , Zubizarreta-Macho Álvaro
Published: January 2025

Several therapeutic methods have been proposed for early class III malocclusion treatment; however, the existing literature does not provide evidence on the most recommended techniques or materials. The aim of the present systematic review and meta-analysis was to summarize the clinical evidence on the efficacy of each method. The PRISMA recommendations were followed. Four databases were searched for articles published up to February 2024. Controlled trials, randomized or non-randomized clinical trials, and prospective or retrospective studies with a control group and a minimum follow-up of 6 months were included. The risk of bias was assessed using the Cochrane collaboration tool. Inconsistency was assessed using the Q test, with a significance level of p < 0.05 and a forest plot. A total of 61 articles were identified, and eight were included in the meta-analysis, which examined three parameters: Sella-Nasion-A (SNA), Sella-Nasion-B (SNB), and A Point-Nasion-B (ANB) values. The meta-analysis was carried out using the random effects model and the inverse variance method. The effect size was determined as the difference between the means of the SNA, SNB, and ANB values in the initial and final intervention groups or between the intervention group and control group. Statistical significance was assessed using the z-test and was declared when p-value < 0.05. The heterogeneity of the meta-analysis was analyzed using the Q test and the I2 statistical index. Publication bias was analyzed using the trim-and-fill method to adjust the skewness of the funnel plot. The risk of bias in the selected studies was assessed using the Cochrane collaboration tool to analyze the methodological quality assessment of the clinical trials. There were statistically significant differences between traditional maxillary disjunction and traction and the different types of Alt-RAMEC protocols, with the latter allowing greater skeletal corrections.
Self-Driven Miniature Sensing Technology Based on Cellulose-Based Triboelectric Nanogenerators in a Wearable Human Health Status Monitoring System
Authors: Xiao Na , He Longqing , Wang Kai
Published: January 2025

The progression of wearable technology has revealed that cellulose-based triboelectric nanogenerators (TENG) possess considerable promise in self-powered micro-sensing technology; this is attributed to their superior biocompatibility, sustainability, and mechanical characteristics. This paper aims to explore the application of the cellulose-based TENG self-powered micro-sensing technology in wearable systems for human health monitoring. First, the working principles and modes of TENG are summarized, along with the characteristics of the cellulose, nanocellulose, cellulose derivatives and the advantages of the cellulose-based TENG. Next, we discuss in detail the applications of the cellulose-based TENG in monitoring physiological parameters, such as heart rate, motion, respiration, and pulse, and we analyze their advantages and challenges in practical applications. Additionally, we explore the integration of the cellulose-based TENG human–machine interaction sensors in health monitoring devices. Finally, we outline the current challenges and future research directions in this field, including the enhancement of triboelectric performance, adaptability to diverse environments, controllable degradability, and multi-scenario real-world applications. This review provides a comprehensive perspective on the application of the cellulose-based TENG self-powered micro-sensing technology in wearable health monitoring systems and offers guidance for future research and development.
Statistical Approach in Personalized Nutrition Exemplified by Reanalysis of Public Datasets
Authors: Ferrario Paola G. , Döring Maik , Ritz Christian
Published: January 2025

In clinical nutrition, it is regularly observed that individuals respond differently to a dietary treatment. Personalized nutrition aims to consider such variability in response by delivering personalized nutritional recommendations. Ideally, the optimal treatment for each individual will be selected and then dispensed according to the specific individual’s characteristics. The aim of this paper is to discuss and apply existing statistical methods, which can be adequately used in the context of personalized nutrition. We discuss the estimation of individualized treatment rules (ITRs) as we wish to favor one out of two interventions. The applicability of the methods is demonstrated by reusing two public datasets: one in the context of a parallel group design and one in the context of a crossover design. The bias of the estimator of the ITRs underlying parameters is evaluated in a simulation study.
Age- and Gender-Based Tongue Volume Variations on Asymptomatic Patients: A Simplified Approach to Form Baseline Data for Obstructive Sleep Apnea
Authors: Baştuğ Betül Tiryaki
Published: January 2025

Background: Tongue anatomy plays a critical role in airway-related disorders such as obstructive sleep apnea (OSA). Understanding variations in tongue volume across age and gender is essential for refining diagnostic and therapeutic strategies. This study aims to establish baseline data for tongue volume using a simplified geometric approach, addressing the gap in large-scale anatomical assessments, specifically in asymptomatic patients without clinical indications of OSA. Materials and Methods: This retrospective cross-sectional study included 120 asymptomatic patients aged 18–75 years, stratified into three age groups (18–40, 41–60, 61+). Tongue volume was estimated using anterior–posterior length, width, and height measurements from neck CT scans, applying a geometric approximation formula. Statistical analysis, including ANOVA and post hoc tests, was used to evaluate differences across age groups and between genders. Regression analysis examined the influence of age and gender on tongue volume. Results: Tongue volume showed a significant decline with advancing age (p < 0.05), with the 61+ age group exhibiting the smallest volumes. Gender differences were pronounced, with males consistently having larger volumes than females (p < 0.05). Post hoc analyses confirmed significant differences between age groups, and regression analysis indicated that gender was a stronger predictor of tongue volume than age. Conclusions: This study highlights the impact of age and gender on tongue volume, emphasizing the need for demographic-specific approaches in the evaluation and management of airway-related conditions. The simplified measurement method offers a practical solution for large-scale studies, providing baseline data for future research and clinical applications. These findings pave the way for personalized diagnostic thresholds and therapeutic strategies in conditions like OSA.
The Duration of Cataract Surgery and the Change in Postoperative Dry Eye Disease Parameters: A Retrospective Cohort Study
Authors: Lee Chia-Yi , Yang Shun-Fa , Chen Yun-Chen , Chang Chao-Kai
Published: January 2025

Objective: The aim of this study was to evaluate the correlation between the duration of cataract surgery and the postoperative dry eye disease (DED) parameters. Methods: A retrospective cohort study was conducted on individuals who received cataract surgery at our institution. In total, 72 and 36 eyes were split into the short and long surgery groups, respectively. The main outcomes were the postoperative tear break-up time (TBUT), the Schirmer II test result, the ocular surface staining score, the DED symptoms, and the presence of meibomian gland dysfunction (MGD). A generalized linear model was employed to compare the changes in the DED parameters between the two groups. Results: The uncorrected visual acuity (UDVA) was significantly better in the short surgery group compared to the long surgery group (p = 0.031). The latter group also demonstrated a significantly shorter TBUT and a higher ocular surface stain score compared to those of the short surgery group (both p < 0.05). The change in the TBUT and ocular surface stain score were significantly higher in the long surgery group than the short surgery group (both p < 0.05). No DED parameters were significantly associated with the postoperative UDVA in the short surgery group (all p > 0.05). However, the TBUT and the ocular surface stain score correlated with worse postoperative UDVA in the long surgery group (both p < 0.05). Conclusions: Operating on a cataract for more than 20 min correlates with a long TBUT and a poor ocular surface staining score, which could influence the postoperative UDVA.