bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determinants of naturalization and invasion of Tetraclinis articulata in eastern Mediterranean drylands: Is it a “superinvader”?
Authors: Cohen Oded , Sheffer Efrat , Bar-Shmuel Nitsan , Weber Gil , Guy Aviv , Avioz Tamir , Osem Yagil 
Published: February 2025

Abstract

Tetraclinis articulata, endangered in the western Mediterranean, is suspected to have become invasive in the eastern Mediterranean. This study assessed its naturalization/invasion status across Israel, where it was planted over 6000 ha in semi-arid and Mediterranean regions. We hypothesized that T. articulata colonizes undisturbed sites with low competition in combination with favourable microhabitat conditions for germination and establishment. We measured the density of regenerating T. articulata saplings in 46 eastern Mediterranean plantation sites up to 60 m away from plantation margins. Saplings were observed in 74% of the sites, of which 79% contained saplings beyond the plantation margins. The density of saplings decreased with distance from the margins and was significantly higher in Mediterranean than in semi-arid sites. Higher sapling densities were associated with tall, dense, woody vegetation formations, northern hillslope aspects with moderate slopes, soft bedrock, high stone/rock cover and absence of livestock grazing. We found that microclimatic refuges act as stepping stones for seedling recruitment, potentially explaining the successful colonization by this slow-growing species in dryland climates. Contrary to the common invader archetype, T. articulata exhibits late successional characteristics, preferentially establishing in well-developed woodlands and forests, in line with the recently defined “superinvader” archetype. Exhibiting superinvader behaviour, the invasion potential of T. articulata in natural eastern Mediterranean dryland ecosystems poses a serious threat. Reducing seed sources regionally, including drastic action such as clearing mature forests to protect biodiversity, is vital to preventing spread, especially in Mediterranean climates, and near woodlands. In the larger scheme of things, afforestation efforts in drylands using exotic drought-resistant tree species must consider this potential outcome.
Modeling dynamic pressure loss by absorption in oleo-pneumatic shock absorbers without separator
Authors: Willich Felix , Holzapfel Florian , Vrabec Jadran 
Published: February 2025

Abstract
A model for the dynamic pressure loss in standard oleo-pneumatic shock absorbers without gas-oil separator for avionics applications is introduced. The dynamics of such a device under load variations are primarily determined by the throttle between the oil chamber and the gas chamber. During operation, gas is absorbed by the oil upon compression and desorbed upon expansion, which are processes that extend over time and entail hysteresis. It is found that the assumption of isothermal conditions is sufficient. An excellent alignment is achieved by the model and the measured hysteresis across diverse drop test scenarios, adjusting a single parameter to a value that is physically reasonable. The standard deviation of the error in pressure is

$${\sigma _{p}=0.49\,\textrm{bar}}$$

σ
p

=
0.49

bar

. Moreover, the model rests on thermodynamic considerations and experimental gas solubility data, while it is consistent with other laboratory data from the literature.
Precision mapping and treatment of spring dead spot in bermudagrass using unmanned aerial vehicles and global navigation satellite systems sprayer technology
Authors: Henderson Caleb , Haak David , Mehl Hillary , Shafian Sanaz , McCall David 
Published: February 2025

Abstract
Spring dead spot is a disease of bermudagrass (Cynodon dactylon L. Pers) caused by Ophiosphaerella spp., of fungi which infect the below ground structures of plants, causing damage to the turf canopy. Previous research suggests that precision management strategies based on manually identified disease within unmanned aerial vehicle (UAV) imagery using GIS software and global navigation satellite systems (GNSS)-equipped sprayers can reduce the fungicide required for spring dead spot management. However, this methodology is time consuming and impractical for golf course superintendents. This paper introduces a novel approach to spring dead spot identification utilizing a custom Python script, the Simple Ophiosphaerella Damage Detector (SODD), to identify and record locations of spring dead spot from UAV imagery using basic feature extraction techniques. Initial tests comparing the outputs from SODD to spring dead spot manually identified by researchers on four fairways, comparisons of K-means cluster maps showed similarities ranging between 71 and 88% although incidence counts were inconsistent. Precision treatment methods based on SODD were evaluated across 16 golf course fairways at three locations in Virginia organized as a randomized complete-block design with four replications and four treatment methods; spot and zonal treatments based on SODD identified incidence and density, respectively, compared against full-coverage and non-treated controls. Applications were made with a Toro Multipro5800 with GeoLink GNSS-equipped sprayer in Fall of 2021. Spot and zonal treatment strategies showed similar control to full-coverage applications (p≤0.001) while reducing the percentage of the fairways treated by 48% and 52%, respectively (p≤0.001). These results highlight the capabilities for SODD as a tool for disease map generation.
Estimation of weed distribution for site-specific weed management—can Gaussian copula reduce the smoothing effect?
Authors: Schatke Mona , Ulber Lena , Kämpfer Christoph , von Redwitz Christoph 
Published: February 2025

Abstract

Purpose
Creating spatial weed distribution maps as the basis for site-specific weed management (SSWM) requires determining the occurrence and densities of weeds at georeferenced grid points. To achieve a field-wide distribution map, the weed distribution between the sampling points needs to be predicted. The aim of this study was to determine the best combination of grid sampling design and spatial interpolation technique to improve prediction accuracy. Gaussian copula as alternative method was tested to overcome challenges associated with interpolating weed densities such as smoothing effects.

Methods
The quality of weed distribution maps created using combinations of different sampling grids and interpolation methods was assessed: Inverse Distance Weighting, different geostatistical approaches, and Nearest Neighbor Interpolation. For this comparison, the weed distribution and densities in four fields were assessed using three sampling grids with different resolutions and arrangements: Random vs. regular arrangement of 40 grid points, and a combination of both grid types (fine grid).

Results
The best prediction of weed distribution was achieved with the Kriging interpolation models based on weed data sampled on the fine grid. In contrast, the lowest performance was observed using the regular grid and the Nearest Neighbor Interpolation. A patchy distribution of weeds did not affect the prediction quality.

Conclusion
Using the Gaussian copula kriging did not result in a reduction of the smoothing effect, which still represents a challenge when employing spatial interpolation methods for SSWM. However, using a randomly distributed raster with a fine resolution could further optimize the precision of weed distribution maps.
Do human-induced habitat changes impact the morphology of a common amphibian, Bufo bufo?
Authors: Bettencourt-Amarante Soline , Abensur Raphaëlle , Furet Robin , Ragon Clara , Herrel Anthony 
Published: February 2025

Abstract
Human activities induce habitat modifications and the intensification of land use including urbanisation and agriculture. Human-modified habitats are often fragmented, generating patches separated by dispersal barriers. In order to cross landscape obstacles, animals need to adapt or show plastic responses allowing effective dispersal and the pursuit of fitness-relevant activities. Due to their limited dispersal capacity and the need for terrestrial and aquatic habitats to complete their biphasic life cycle, amphibians can be expected to be particularly vulnerable to changes in the landscape. Yet data to test these ideas remain relatively scarce. To test whether human-induced habitat modifications impact the morphology of animals with low dispersal ability we measure 15 morphological traits on 137 common toads (Bufo bufo) across four habitat types represented by two or three independent sites across the Ile de France region. The results shown morphological differences among habitat types and sexes. Animals show habitat specific morphologies that may allow them to survive in human-modified habitats. Moreover, females have larger heads possibly to avoid trophic resource competition with males. Males, on the other hand show longer limbs possibly related to their greater movements when finding females during the reproductive season. Overall, our results that animals living in different habitat types are morphologically different with differences between natural and urban habitat being the greatest. Whether these differences are due to local adaptation or plastic responses remains to be investigated.
Digital ecosystems and their influence on business relationships
Authors: Baptista Cristina Sales , Nunes Danilo 
Published: February 2025

Abstract
Our study focuses on digitalization and its effects on business relationships, particularly on the innovative aspect of how the development of digital ecosystems influences these relationships. Digital ecosystems are defined as socio-technical environments in which individuals, organizations, and digital technologies develop collaborative and competitive relationships to create value for their end customers through shared digital platforms. The main characteristics of a digital ecosystem include the existence of digital platforms and symbiosis, which refers to the interdependence between business ecosystems. Methodologically, we adopted a case study research strategy to capture the nature of the activities, resources, and actors involved, as well as the effect of digital ecosystems on the development of business relationships. This study demonstrates that digital ecosystems enhance collaboration and influence companies’ activities and resource ties by enabling real-time communication and information sharing among different actors. This collaboration extends to entities from different industries and digital platforms, which effectively integrate data between companies in real time. Furthermore, actors embedded in digital ecosystems gain several advantages, such as cost reduction, lower network latency (due to the proximity between actors), greater flexibility in establishing new connections within a shorter time frame, and accelerated time-to-market (due to the availability of multiple actors within the same environment). Moreover, actors seek to foster both cooperative and competitive relationships among participating companies, allowing each entity to purchase or transact services in a significantly simpler and more efficient manner.
Update on Pediatric Hepatitis C Infection
Authors: Ferreira Johanna , Sheflin-Findling Shari 
Published: February 2025

Abstract

Purposeof Review
Hepatitis C virus (HCV) infections continue to steadily increase in the United States and remain a major public health challenge. This review aims to provide a comprehensive overview of HCV infection in children, focusing on recent advancements in screening, diagnosis, and treatment.

Recent Findings
Effective screening strategies, including universal screening of pregnant women and nucleic acid testing for all perinatally exposed infants at 2 to 6 months of age, have been implemented to identify infected individuals early. Direct-acting antiviral agents have revolutionized treatment, offering high cure rates for children of all ages.

Summary
Despite significant progress, challenges remain in achieving HCV elimination. These include the need for improved access to testing and treatment, as well as ongoing efforts to develop a preventive vaccine. Continued research and implementation of effective strategies are essential to reduce the burden of HCV infection.
Is there any effect of hcc location on selective internal radiation therapy with 90yttrium response?
Authors: Akgun Elife , Erdim Cagrı , Ibicioglu Burcu , Guzelbey Tevfik , Akkas Burcu Esen , Kılıckesmez Ozgur 
Published: February 2025

Abstract

Background
We planned this retrospective study to evaluate the effect of the central vs peripheral location effect on the success of selective internal radiation therapy (SIRT) with 90Yttrium-90 (90Y) glass microspheres in hepatocellular carcinomas (HCC).

Material and methods
Thirty-eight patients diagnosed with HCC who were eligible for SIRT with 90Y glass microspheres were included in this study. The location being central versus peripheral was defined as explained: Straight lines through the bifurcation of the right and left branches of the portal vein to the center of the HCC and the peripheral surface of the liver were traced on the same plane. The coefficient was determined as a ratio of the center of the HCC to the distance from the hilum of the liver at the portal vein bifurcation. Value under ½ accepted as central location (Group 1, n = 17), over ½ values are accepted as peripheral location (Group 2, n = 21). Treatment responses were analyzed after 2 months of the treatment with magnetic resonance imaging, and 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT) for FDG-avid ones. Differences in treatment responses rates, treatment approach, the absorbed doses and the volumes of each liver segments between groups were investigated.

Results
In Group 1; mean age was 67. In 5 cases split infusion, in 10 cases tumor selective treatment approach were applied. According to PERCIST/mRECIST criteria treatment responses categories: complete response in 2/1 cases, partial response in 7/9 cases, stable disease in 3/4 cases, progressive diseases in 2/3 cases; respectively. AFP value decreased in 2 cases, increased in 7 cases, and was stable in 1 case. Mean absorbed doses were 347.9 Gy for tumor, 140.6 Gy for perfused normal tissue, and 26.1 Gy for the normal liver. In Group 2; the mean age was 71.5. In 5 cases split infusion, and in 1 case non-selective treatment approach were applied. According to PERCIST/mRECIST criteria treatment responses categories: complete response in 7/6 cases, partial response in 7/10 cases, stable disease in 2/2 cases, and progressive diseases in 3/3 cases; respectively. AFP value decreased in 9 cases, increased in 2 cases, and was stable in 2 cases. Mean absorbed doses were 495.9 Gy for tumor, 134 Gy for perfused normal tissue, and 17.3 Gy for the normal liver.There is no statistically significant difference in terms of gender, treatment response rates, tumor volumes, perfuse tissue volumes between 2 groups. However, tumor-selective approach and absorbed doses of the perfused normal tissue and the tumor were significantly higher in Group 2 (p = 0.007, 0.04, and 0.02; respectively).

Conclusion
Contrary to expectation, centrally located HCCs could be treated as successfully as peripherally located HCCs. However, the complete response rate in the peripheral located tumor is more frequent than centrally located ones.
IL-1β and associated molecules as prognostic biomarkers linked with immune cell infiltration in colorectal cancer: an integrated statistical and machine learning approach
Authors: Sahoo Karishma , Sundararajan Vino 
Published: February 2025

Abstract

Purpose
Colorectal cancer (CRC) is the third most common cancer globally, necessitating novel biomarkers for early diagnosis and treatment. This study proposes an efficient pipeline leveraging an integrated bioinformatics and machine learning framework to enhance the identification of diagnostic and prognostic biomarkers for CRC.

Methods
A selection of methylated differentially expressed genes (MeDEGs) and features (genes) was made using both statistical and Machine learning (ML) approaches from publically available datasets. These genes were subjected to STRING network construction and hub genes estimation, separately. Also, essential miRNAs (micro-RNAs) and TFs (Transcription factors) as regulatory elements were revealed and findings were validated through scRNA-seq analysis, promoter methylation, gene expression levels correlated with pathological stage, and interaction with tumor-infiltrating immune cells.

Results
Through an integrated analysis pipeline, we identified 27 hub genes, among which CTNNB1, GSK3B, IL-1β, MYC, PXDN, TP53, EGFR, SRC, COL1A1, and TGBF1 showed better diagnostic behaviour. Machine learning approach includes the development of K-Nearest Neighbors (KNN), Artificial Neural Networks (ANN), and Random Forest (RF) models using TCGA datasets, achieving an accuracy range between 99 and 100%. The Area Under the Curve (AUC) value for each model is 1.00, signifying good classification performance. The high expression of some diagnostic genes was associated with poor prognosis, concluding IL-1β as both a prognostic and diagnostic biomarker. Additionally, the NF-κB and microRNAs (miR-548d-3p, miR-548-ac) and TFs (NFκB and STAT5A) play a major role in the comprehensive regulatory network for CRC. Furthermore, hub genes such as IL-1β, TGFB1, and COL1A1 were significantly correlated with immune infiltrates, suggesting their potential role in CRC progression.

Conclusion
Overall, the elevated expression of IL-1β coupled with abnormal DNA methylation, and its consequent effect on the PI3K/Akt signaling pathway are relevant prognostic and therapeutic marker in CRC. Additional molecular candidates reveal insights into the epigenetic regulatory targets of CRC and their association with immune cell infiltration.
A 10-year bibliometric analysis in the field of osteosarcoma treatment from 2014 to 2023
Authors: Shen Yiguo , Shao Xiaobo , Chen Jiansong , Tang Xin 
Published: February 2025

Abstract

Objective
This paper aims to explore the research hot spot and development trend in osteosarcoma treatment using a bibliometric method based upon Web of Science Core Collection (WoSCC) platform over the last decade.

Methods
The literature related to osteosarcoma and cure which were published from January 2014 to December 2023 were retrieved from the database of WoSCC and made an overall analysis for the papers published including number of articles, distribution of countries and institutions, author information, and keywords, with the CiteSpace 6.2.R5.

Results
A total of 3131 papers were retrieved, including 2601 articles and 530 reviews, and the number of papers published has been increasing year by year in the last decade. There were 415 countries and 10,719 research institutions participating into the study. China’s output of literature was the highest relying on its 1490 papers published, followed by The United States (548 papers). Shanghai Jiaotong university had the largest number of papers published (121 papers) and Central South University ranked second (82 papers). A total of 16,816 authors participated in the study. The number of the paper published by Massimo Serra of the Rizzoli Orthopaedics Institute was the largest (27 papers), followed by Dominique Heymann of the University of Sheffield (20 papers). The visualization analysis of keywords by CiteSpace software showed that the drug resistance, drug delivery, tumor tissue engineering and gene expression have become hotspots in the field of osteosarcoma treatment. Drug resistance significantly limits the effectiveness of current cancer treatments. Drug delivery technology not only enhances the targeting and efficacy of drugs but also helps to overcome drug resistance. The stem cells, targeted therapy, and tumor microenvironment represent the new research trends. In particular, the tumor microenvironment plays a key role in tumor development, progression, and drug resistance, and it offers numerous potential therapeutic targets.

Conclusion
Our investigation has identified key research foci and hotspots in osteosarcoma treatment, including drug resistance mechanisms, innovations in drug delivery technology, stem cell development, tumor microenvironment analysis, the development of novel therapies, and the clinical translation of tumor tissue engineering.
A multilevel bridge corrosion detection method by transformer-based segmentation in a stitched view
Authors: Lu Ziyue , Jiang Tengjiao , Slavič Janko , Frøseth Gunnstein T. 
Published: February 2025

Abstract
Corrosion is one of the main damage mechanisms in civil engineering structures today. Rapid identification and accurate assessment of corrosion in structures are essential to ensure the efficient allocation of limited funds for the maintenance and renewal of existing structures. Vision-based neural networks have been widely used in corrosion detection, in which convolutional neural network (CNN)-like models remain dominant. However, these conventional network models exhibit a saturating performance. Because of the self-attention mechanism, the transformer is the newest breakthrough in computer vision and is becoming state of the art. As the complexity of structures increases, transformer-based methods have no saturating performance. This study proposes a corrosion localization and evaluation architecture for a larger view based on semantic segmentation and image stitching for automatic localization and diagnosis of corrosion from stitched images. The experimental results showed that the proposed method achieved better corrosion detection performance (F1-score = 68.2%) than that of the mainstream CNN-like models U-Net (F1-score = 61.8%) and DeepLabV3 + (F1-score = 60.1%). Image stitching is utilized for corrosion segmentation in larger view images, and the field test shows that the proposed architecture could stitch corrosion prediction from different images.
Value of focused lung ultrasound in diagnosing and monitoring pneumothorax after CT-guided lung biopsy
Authors: Metzler Emma Katrine , Everløff Nina , Juul Amanda Dandanell , Laursen Christian Borbjerg , Graumann Ole , Pietersen Pia Iben 
Published: February 2025

Abstract

Background
Pneumothorax is a common complication after CT-guided transthoracic lung biopsy. Pneumothorax is most often diagnosed with a conventional chest X-ray after a two-hour observation period. Ultrasound has been shown to be superior to conventional X-rays in diagnosing pneumothorax in some settings and it can be repeated without radiation exposure.

Purpose
The aim of the study was firstly to explore the sensitivity and specificity of thoracic ultrasound compared to conventional chest x-ray following CT-guided transthoracic lung biopsy, and secondly to investigate the dynamic changes of pneumothorax size using ultrasound.

Methods
This prospective study was conducted at Odense University Hospital in the Department of Radiology. Adult patients undergoing CT-guided lung biopsy were eligible for inclusion. A total of 26 patients were included in the study and were scanned five times in sitting upright and supine positions during the two-hour observation time using the FLUS Protocol.

Results
Pneumothorax was diagnosed via chest x-ray in 11 (42%) patients. With the patient in an upright position, the ultrasound had a sensitivity of 63.6% and a specificity of 93.3%. These numbers rose to 72.3% and 100% in the supine position. Monitoring the pneumothoraces showed a slight increase in size during the two hours.

Conclusions
Ultrasound can be used to diagnose pneumothorax after CT-guided lung biopsy. All pneumothoraxes that were identified by ultrasound were detected within the first 30 min. The dynamic changes of pneumothoraxes showed that the size of the pneumothorax did not increase to a level where the patient needed intervention or admittance.