bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metastable cellular structures govern localized corrosion damage development in additive manufactured stainless steel
Authors: DelVecchio Evan , Liu Tiffany , Chang Yen-Ting , Nie Yuheng , Eslami Maryam , Charpagne Marie A. 
Published: May 2024

AbstractThe rapid solidification associated with additive manufacturing (AM) leads to complex microstructures with peculiar features amongst which cellular solidification structures are the most remarkable. These metastable structures possess a clear segregation pattern dictated by the solidification pathway of the alloy and are bounded by dislocation walls. While they confer exceptional strength and ductility to AM 316L stainless steel, their effect on localized corrosion in chloride environments remains to be established. Here, we employ correlative electron microscopy to reveal coupled chemical, electrochemical, and crystallographic effects on localized corrosion attack and its development. We show that the Cr and Mo-depleted interior of the cellular solidification structures dissolves selectively, giving rise to an intricate damage morphology, that is directly related to the underlying crystallographic orientation. Whereas surface observations only reveal apparently shallow micrometer-size cavities, 3D tomography via focused ion beam serial-sectioning shows a high degree of connectivity between these features underneath the surface. We reveal this intricate morphology, propose a formation mechanism, and discuss alloy design guidelines to mitigate this phenomenon.
Content-based image retrieval of Indian traditional textile motifs using deep feature fusion
Authors: Varshney Seema , Singh Sarika , Lakshmi C. Vasantha , Patvardhan C. 
Published: May 2024

AbstractIn the fast-paced fashion world, unique designs are like early birds, grabbing attention as online shopping surges. Fabric texture plays an immense role in selecting the perfect design. Indian Traditional textile motifs are pivotal, showing rich cultural origins and attracting worldwide art fanatics. Yet, technology-driven abstract forms are posing a challenge for them. The decline of handmade artistic ability due to computerization is concerning. Crafting new designs associated with the latest trends is time- consuming and requires diligence. In this work an interactive CBIR (content-based image retrieval) system is presented. It utilizes deep features from InceptionV3 and InceptionResNetV2 models to match query designs with a database of traditional Indian textiles. Its performance is tested with Caltech-101, Corel-1K state-of-the-art datasets, and Indian Textiles datasets and the results are shown to be finer than the existing approaches. The similarity-based fine-grained saliency maps (SBFGSM) approach is employed to visualize the importance of features. Our approach combines deep feature fusion with PCA dimensionality reduction and speeds up search using a clustering approach. Relevance feedback is employed to refine the retrievals. This tool is expected to benefit designers by accelerating the design cycles by bridging the gap between human creativity and A.I. assistance.
An eco-friendly and cost-effective HPTLC method for quantification of COVID-19 antiviral drug and co-administered medications in spiked human plasma
Authors: Ghozzy Ekram A. , El-Enany Nahed M. , Tolba Manar M. , El Abass Samah Abo 
Published: May 2024

AbstractThe coronavirus-2 has led to a global pandemic of COVID-19 with an outbreak of severe acute respiratory syndrome leading to worldwide quarantine measures and a rise in death rates. The objective of this study is to propose a green, sensitive, and selective densitometric method to simultaneously quantify remdesivir (REM) in the presence of the co-administered drug linezolid (LNZ) and rivaroxaban (RIV) in spiked human plasma. TLC silica gel aluminum plates 60 F254 were used as the stationary phase, and the mobile phase was composed of dichloromethane (DCM): acetone (8.5:1.5, v/v) with densitometric detection at 254 nm. Well-resolved peaks have been observed with retardation factors (Rf) of 0.23, 0.53, and 0.72 for REM, LNZ, and RIV, respectively. A validation study was conducted according to ICH Q2 (R1) Guidelines. The method was rectilinear over the concentration ranges of 0.2–5.5 μg/band, 0.2–4.5 μg/band and 0.1–3.0 μg/band for REM, LNZ and RIV, respectively. The sensitivities of REM, LIN, and RIV were outstanding, with quantitation limits of 128.8, 50.5, and 55.8 ng/band, respectively. The approach has shown outstanding recoveries ranging from 98.3 to 101.2% when applied to pharmaceutical formulations and spiked human plasma. The method’s greenness was assessed using Analytical Eco-scale, GAPI, and AGREE metrics.
Exploring virtual reality object perception following sensory-motor interactions with different visuo-haptic collider properties
Authors: Girondini Matteo , Montanaro Massimo , Gallace Alberto 
Published: May 2024

AbstractInteracting with the environment often requires the integration of visual and haptic information. Notably, perceiving external objects depends on how our brain binds sensory inputs into a unitary experience. The feedback provided by objects when we interact (through our movements) with them might then influence our perception. In VR, the interaction with an object can be dissociated by the size of the object itself by means of ‘colliders’ (interactive spaces surrounding the objects). The present study investigates possible after-effects in size discrimination for virtual objects after exposure to a prolonged interaction characterized by visual and haptic incongruencies. A total of 96 participants participated in this virtual reality study. Participants were distributed into four groups, in which they were required to perform a size discrimination task between two cubes before and after 15 min of a visuomotor task involving the interaction with the same virtual cubes. Each group interacted with a different cube where the visual (normal vs. small collider) and the virtual cube's haptic (vibration vs. no vibration) features were manipulated. The quality of interaction (number of touches and trials performed) was used as a dependent variable to investigate the performance in the visuomotor task. To measure bias in size perception, we compared changes in point of subjective equality (PSE) before and after the task in the four groups. The results showed that a small visual collider decreased manipulation performance, regardless of the presence or not of the haptic signal. However, change in PSE was found only in the group exposed to the small visual collider with haptic feedback, leading to increased perception of the cube size. This after-effect was absent in the only visual incongruency condition, suggesting that haptic information and multisensory integration played a crucial role in inducing perceptual changes. The results are discussed considering the recent findings in visual-haptic integration during multisensory information processing in real and virtual environments.
Performance of IRI 2016 model in predicting total electron content (TEC) compared with GPS-TEC over East Africa during 2019–2021
Authors: Sulungu Emmanuel D. 
Published: May 2024

AbstractThis study evaluated the applicability of IRI-2016 model in predicting GPS TEC using the monthly means of the five (5) quiet days for equinoxes and solstices months. GPS-derived TEC data were obtained from the IGS network of ground based dual frequency GPS receivers from three stations [(KYN3 0.53° S, 38.53° E; Geom. Lat. 3.91.63° S), (MBAR 0.60° S, 30.74° E; Geom. Lat. 2.76° S) and HOID 1.45° S, 31.34° E; Geom. Lat. 3.71° S]. All the three options for topside Ne of IRI-2016 model and ABT-2009 for bottomside thickness have been used to compute the IRI TEC. The results were compared with the GPS TEC measurements. Correlation Coefficients between the two sets of data, the Root-Mean Square Errors of the IRI-TEC from the GPS-TEC, and the percentage RMSE of the IRI-TEC from the GPS-TEC have been computed. In general, the IRI-2016 model underestimated GPS-TEC during the nighttime, whereas the model overestimated GPS-TEC values during the daytime. At most of the stations and during all seasons where data were available, correlation coefficient was above 0.9, which is quite strong. The variation of O/N2 ratio may potentially be the cause of the IRI TEC deviation from the GPS TEC. This variation arises from lower thermosphere plasma drift that moves upward.
A non-invasive tool to collect small intestine content in post weaning pigs: validation study
Authors: García Viñado Inés , Correa Federico , Trevisi Paolo , Bee Giuseppe , Ollagnier Catherine 
Published: May 2024

AbstractThe Capsule for Sampling (CapSa) is an ingestible capsule that collects small intestine content while transiting through the natural digestive pathway. In this study, 14 Swiss Large White pigs weighing less than 12 kg (Category < 12 kg) and 12 weighing between 12 and 20 kg (Category [12–20 kg]) were given two CapSas and monitored for three days. The animals were euthanized for post-mortem sampling, allowing us to directly obtain gut microbiota samples from the gastrointestinal tract. This post-mortem approach enabled a direct comparison between the microbial content from the gut and the samples collected via the CapSas, and it also facilitated precise identification of the CapSas’ sampling sites within the gastrointestinal tract. For the category under 12 kg, only 2.3% of the administered CapSas were recovered from the feces. In contrast, in the 12–20 kg category, 62.5% of the CapSas were successfully retrieved from the feces within 48 h. Of these recovered CapSas, 73.3%—equating to 11 capsules from eight pigs—had a pH > 5.5 and were therefore selected for microbiome analysis. Bacterial composition of the CapSas was compared with that of the three segments of the small intestine, the large intestine and feces of the corresponding pig. The results were tested using a PERMANOVA model (Adonis) including sample type as a factor, and then pairwise comparisons were made. The bacterial composition found in the CapSas differed from that of the large intestine and feces (P < 0.01), while it did not differ from the first segment of the small intestine (P > 0.10). This study provides evidence that the CapSa effectively samples the intestinal microbiota from the upper section of the small intestine in post-weaning pigs. Furthermore, it was found that the collection of CapSas could only be successfully achieved in pigs classified within the heavier weight category.
A novel low-cost uterine balloon tamponade kit to tackle maternal mortality in low-resource settings
Authors: Candidori Sara , Osouli Kasra , Graziosi Serena , Zanini Alberto Antonio , Costantino Maria Laura , De Gaetano Francesco 
Published: May 2024

AbstractThe 3.1 target of the Sustainable Development Goals of the United Nations aims to reduce the global maternal mortality ratio to less than 70 maternal deaths per 100,000 live births by 2030. The last updates on this target show a significant stagnation in the data, thus reducing the chance of meeting it. What makes this negative result even more serious is that these maternal deaths could be avoided through prevention and the wider use of pharmacological strategies and devices to stop postpartum haemorrhage (PPH). PPH is the leading obstetric cause of maternal mortality in low- and middle-income countries (LMICs). Despite low-cost devices based on the uterine balloon tamponade (UBT) technique are already available, they are not safe enough to guarantee the complete stop of the bleeding. When effective, they are too expensive, especially for LMICs. To address this issue, this study presents the design, mechanical characterisation and technology assessment performed to validate a novel low-cost UBT kit, particularly a novel component, i.e., the connector, which guarantees the kit’s effectiveness and represents the main novelty. Results proved the device’s effectiveness in stopping PPH in a simulated scenario. Moreover, economic and manufacturing evaluations demonstrated its potential to be adopted in LMICs.
Unraveling the phylogenetics of genetically closely related species, Haemaphysalis japonica and Haemaphysalis megaspinosa, using entire tick mitogenomes and microbiomes
Authors: Moustafa Mohamed Abdallah Mohamed , Mohamed Wessam M. A. , Chatanga Elisha , Naguib Doaa , Matsuno Keita , Gofton Alexander W. , Barker Stephen C. , Nonaka Nariaki , Nakao Ryo 
Published: May 2024

AbstractTicks have a profound impact on public health. Haemaphysalis is one of the most widespread genera in Asia, including Japan. The taxonomy and genetic differentiation of Haemaphysalis spp. is challenging. For instance, previous studies struggled to distinguish Haemaphysalis japonica and Haemaphysalis megaspinosa due to the dearth of nucleotide sequence polymorphisms in widely used barcoding genes. The classification of H. japonica japonica and its related sub-species Haemaphysalis japonica douglasi or Haemaphysalis jezoensis is also confused due to their high morphological similarity and a lack of molecular data that support the current classification. We used mitogenomes and microbiomes of H. japonica and H. megaspinosa to gain deeper insights into the phylogenetic relationships and genetic divergence between two species. Phylogenetic analyses of concatenated nucleotide sequences of protein-coding genes and ribosomal DNA genes distinguished H. japonica and H. megaspinosa as monophyletic clades, with further subdivision within the H. japonica clade. The 16S rRNA and NAD5 genes were valuable markers for distinguishing H. japonica and H. megaspinosa. Population genetic structure analyses indicated that genetic variation within populations accounted for a large proportion of the total variation compared to variation between populations. Microbiome analyses revealed differences in alpha and beta diversity between H. japonica and H. megaspinosa: H. japonica had the higher diversity. Coxiella sp., a likely endosymbiont, was found in both Haemaphysalis species. The abundance profiles of likely endosymbionts, pathogens, and commensals differed between H. japonica and H. megaspinosa: H. megaspinosa was more diverse.
MRI-based radiomics for predicting histology in malignant salivary gland tumors: methodology and “proof of principle”
Authors: Khodabakhshi Zahra , Motisi Laura , Bink Andrea , Broglie Martina A. , Rupp Niels J. , Fleischmann Maximilian , von der Grün Jens , Guckenberger Matthias , Tanadini-Lang Stephanie , Balermpas Panagiotis 
Published: May 2024

AbstractDefining the exact histological features of salivary gland malignancies before treatment remains an unsolved problem that compromises the ability to tailor further therapeutic steps individually. Radiomics, a new methodology to extract quantitative information from medical images, could contribute to characterizing the individual cancer phenotype already before treatment in a fast and non-invasive way. Consequently, the standardization and implementation of radiomic analysis in the clinical routine work to predict histology of salivary gland cancer (SGC) could also provide improvements in clinical decision-making. In this study, we aimed to investigate the potential of radiomic features as imaging biomarker to distinguish between high grade and low-grade salivary gland malignancies. We have also investigated the effect of image and feature level harmonization on the performance of radiomic models. For this study, our dual center cohort consisted of 126 patients, with histologically proven SGC, who underwent curative-intent treatment in two tertiary oncology centers. We extracted and analyzed the radiomics features of 120 pre-therapeutic MRI images with gadolinium (T1 sequences), and correlated those with the definitive post-operative histology. In our study the best radiomic model achieved average AUC of 0.66 and balanced accuracy of 0.63. According to the results, there is significant difference between the performance of models based on MRI intensity normalized images + harmonized features and other models (pvalue < 0.05) which indicates that in case of dealing with heterogeneous dataset, applying the harmonization methods is beneficial. Among radiomic features minimum intensity from first order, and gray level-variance from texture category were frequently selected during multivariate analysis which indicate the potential of these features as being used as imaging biomarker. The present bicentric study presents for the first time the feasibility of implementing MR-based, handcrafted radiomics, based on T1 contrast-enhanced sequences and the ComBat harmonization method in an effort to predict the formal grading of salivary gland carcinoma with satisfactory performance.
Investigation of heat stress responses and adaptation mechanisms by integrative metabolome and transcriptome analysis in tea plants (Camellia sinensis)
Authors: Huang Feiyi , Lei Yu , Duan Jihua , Kang Yankai , Luo Yi , Ding Ding , Chen Yingyu , Li Saijun 
Published: May 2024

AbstractExtreme high temperature has deleterious impact on the yield and quality of tea production, which has aroused the attention of growers and breeders. However, the mechanisms by which tea plant varieties respond to extreme environmental heat is not clear. In this study, we analyzed physiological indices, metabolites and transcriptome differences in three different heat-tolerant tea plant F1 hybrid progenies. Results showed that the antioxidant enzyme activity, proline, and malondialdehyde were significantly decreased in heat-sensitive ‘FWS’ variety, and the accumulation of reactive oxygen molecules such as H2O2 and O2− was remarkably increased during heat stress. Metabolomic analysis was used to investigate the metabolite accumulation pattern of different varieties in response to heat stress. The result showed that a total of 810 metabolites were identified and more than 300 metabolites were differentially accumulated. Transcriptional profiling of three tea varieties found that such genes encoding proteins with chaperon domains were preferentially expressed in heat-tolerant varieties under heat stress, including universal stress protein (USP32, USP-like), chaperonin-like protein 2 (CLP2), small heat shock protein (HSP18.1), and late embryogenesis abundant protein (LEA5). Combining metabolomic with transcriptomic analyses discovered that the flavonoids biosynthesis pathway was affected by heat stress and most flavonols were up-regulated in heat-tolerant varieties, which owe to the preferential expression of key FLS genes controlling flavonol biosynthesis. Take together, molecular chaperons, or chaperon-like proteins, flavonols accumulation collaboratively contributed to the heat stress adaptation in tea plant. The present study elucidated the differences in metabolite accumulation and gene expression patterns among three different heat-tolerant tea varieties under extreme ambient high temperatures, which helps to reveal the regulatory mechanisms of tea plant adaptation to heat stress, and provides a reference for the breeding of heat-tolerant tea plant varieties.
Prediction method for the tension force of support ropes in flexible rockfall barriers based on full-scale experiments and numerical analysis
Authors: Qi Xin , Zhao Lei , Meng Qing-Cheng 
Published: May 2024

AbstractThis paper proposes a prediction method for the tension force of support ropes in flexible rockfall barriers. The method is based on two full-scale model tests with an impact energy of 3000 kJ, as well as 36 set numerical models featuring varying lengths and impact energies. From the results of full scale tests and numerical models, it is inferred that the tension force at the end of the support rope is significantly less than that at the point of impact, exhibiting an approximate Gaussian attenuation distribution with propagation distance. To account for the attenuation of tensile forces in support ropes, a tensile attenuation coefficient is defined. Through comparative analysis of data obtained from 36 models with varying impact energies and propagation distances, the average attenuation coefficient for the upper support rope is determined to be approximately 0.7, while the average coefficient for the lower support rope is around 0.8. Utilizing the least squares method, a prediction method for the tension force of support ropes in flexible rockfall barriers is established. This method takes into account both the propagation distance and impact energy, enabling accurate predictions of the tensile behavior of the ropes under different conditions. This prediction model provides valuable insights for engineers in the design and optimization of these flexible barriers for rockfall mitigation.
Enhancing surface drainage mapping in eastern Canada with deep learning applied to LiDAR-derived elevation data
Authors: Bilodeau Mathieu F. , Esau Travis J. , Zaman Qamar U. , Heung Brandon , Farooque Aitazaz A. 
Published: May 2024

AbstractAgricultural dykelands in Nova Scotia rely heavily on a surface drainage technique called land forming, which is used to alter the topography of fields to improve drainage. The presence of land-formed fields provides useful information to better understand land utilization on these lands vulnerable to rising sea levels. Current field boundaries delineation and classification methods, such as manual digitalization and traditional segmentation techniques, are labour-intensive and often require manual and time-consuming parameter selection. In recent years, deep learning (DL) techniques, including convolutional neural networks and Mask R-CNN, have shown promising results in object recognition, image classification, and segmentation tasks. However, there is a gap in applying these techniques to detecting surface drainage patterns on agricultural fields. This paper develops and tests a Mask R-CNN model for detecting land-formed fields on agricultural dykelands using LiDAR-derived elevation data. Specifically, our approach focuses on identifying groups of pixels as cohesive objects within the imagery, a method that represents a significant advancement over pixel-by-pixel classification techniques. The DL model developed in this study demonstrated a strong overall performance, with a mean Average Precision (mAP) of 0.89 across Intersection over Union (IoU) thresholds from 0.5 to 0.95, indicating its effectiveness in detecting land-formed fields. Results also revealed that 53% of Nova Scotia’s dykelands are being used for agricultural purposes and approximately 75% (6924 hectares) of these fields were land-formed. By applying deep learning techniques to LiDAR-derived elevation data, this study offers novel insights into surface drainage mapping, enhancing the capability for precise and efficient agricultural land management in regions vulnerable to environmental changes.