bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synergizing AI with Geology: Exploring VisionTransformers for Rock Classification
Authors: Maheen Anfal , Vijayan Vidya , Sivan Shailesh 
Published: August 2024

Abstract

Automated rock identification is a critical domain within geosciences, offering significant advancements over traditional manual methods. This study explores the benefits of automation in rock identification, highlighting improvements in speed, efficiency, consistency, and accuracy. Such advancements facilitate large-scale geological surveys and allow for the seamless integration of various geoscientific data, yielding novel insights into Earth’s geology and resources. The research presents a robust model that achieves an impressive accuracy rate of 88.00%, outperforming conventional Convolutional Neural Networks (CNN) and Transfer Learning approaches. A comprehensive analysis of performance metrics, confusion matrices, and ROC-AUC curves demonstrates the model’s robustness and precision in classifying different rock types. Despite its success, the study acknowledges the challenges in accurately classifying Basalt and suggests potential solutions such as data augmentation and incorporating domain-specific knowledge. The conclusion emphasizes the need for future research to address class imbalances and to adopt more advanced techniques for feature extraction and classification, aiming to further refine the model’s accuracy and applicability in automated rock identification
Environmental yeasts differentially impact the development and oviposition behavior of the Asian tiger mosquito Aedes albopictus
Authors: Malassigné Simon , Laÿs Mathieu , Vallon Laurent , Martin Edwige , Vigneron Aurélien , Van Vân Tran , Minard Guillaume , Moro Claire Valiente , Luis Patricia 
Published: August 2024

Abstract

Background
While the Asian tiger mosquito (Aedes albopictus), a known vector of many arboviruses, establishes symbiotic associations with environmentally acquired yeasts, their impact on mosquito biology remains poorly investigated. To better understand these associations, we hypothesized that water-borne yeasts colonizing the larval gut differentially support mosquito development based on their capacity to produce riboflavin or recycle nitrogen waste into proteins by secreting uricase, as B vitamins and amino acids are crucial for mosquito development. To address this hypothesis, we used axenic and gnotobiotic insects to gauge the specific impact of different environmental yeasts on Ae. albopictus development and survival. We then evaluated whether the observed variations across yeast species could be linked to differential uricolytic activities and varying quantities of riboflavin and proteins in insecta. Finally, given that mosquito breeding site selection favors conditions that enhance offspring performance, we tested whether yeasts that promote faster development mediate oviposition site selection by gravid females.
Results
Differences in mosquito development times were observed based on the environmental yeast used. Yeasts like Rhodotorula mucilaginosa, Aureobasidium pullulans, and Wickerhamomyces anomalus promoted rapid development and were associated with improved survival. Conversely, yeasts such as Torulaspora delbrueckii and Martiniozyma asiatica, which led to slower development, produced smaller adults. Notably, R. mucilaginosa, which promoted the fastest development, provided higher riboflavin intakes and might enhance nitrogenous waste recycling and protein synthesis through strong uricolytic activity. Behavioral experiments indicated that yeasts promoting rapid development attract gravid females.
Conclusions
Our findings highlight that a set of environmental yeasts present in natural larval breeding sites can be associated with improved mosquito development and survival by enhancing nutritional intake, thereby attracting gravid females. Variations in mosquito development time are likely linked to the differential levels of riboflavin production and nitrogenous waste recycling capacities among yeast species. This study opens new perspectives on the trophic interactions between mosquitoes and their mycobiota, emphasizing the importance of nitrogen-containing molecules such as essential amino acids, proteins or vitamins provided by the mycobiota.
An Improved Current Differencing Transconductance Amplifier with Dual Input Dual Output Operation and its Potential Application
Authors: Rana Prerna , Ranjan Ashish 
Published: August 2024

Abstract

This research article presents an extended Current Differencing Transconductance Amplifier (CDTA) designed with a Flipped Voltage Follower (FVF) and an Arbel-Goldminz OTA (AG-OTA), and named Dual Input Dual Output (DIDO-CDTA). The trans-conductance (gm) of the DIDO-CDTA can be electronically tuned, offering practical implications for signal processing circuits. The entire structure operates on a 0.6V supply voltage. The workability of the DIDO-CDTA is validated through DC and AC analysis using the Cadence Virtuoso simulator with 0.18 µm gpdk technology. The designed active block is also used to implement Low Pass Filter (LPF) and High Pass Filter (HPF) using the concept of Wave Active Filter (WAF) and dual-mode integrator circuits.
The genetic associations between gut microbiota and menstruation quality of life impacts in the East Asian women
Authors: Zhou Yuhang , Wang Yue , Feng Yun , Sun Tao , Xu Junnan 
Published: August 2024

Abstract

Background Menstruation affects the physiological and psychological health of East Asian women, imposing burdens on their daily lives and work. The gut microbiota has been found to improve various diseases. The study used Mendelian randomization to exploratorily discuss the causal effects of gut microbiota on the menstruation quality of life impacts. Methods According to the predefined threshold, independent genetic variants significantly linked to 119 bacterial genera in the gut were extracted as instrumental variables. The inverse variance weighted (IVW) was utilized as the primary analysis method, supplemented by MR-Egger and Weighted median methods. Effect estimates were assessed primarily using the odds ratios (OR) and 95% confidence intervals (95%CI). In addition, sensitivity analyses (heterogeneity, horizontal pleiotropy, and outliers) were implemented to evaluate the robustness and accuracy of the findings. Results Causal effects were found between 28 bacterial genera and 13 menstruation quality of life impacts. Based on OR, 18 bacterial genera were identified as risk factors, while 10 were identified as protective factors. Furthermore, sensitivity analysis did not detect heterogeneity, horizontal pleiotropy, or outliers. Conclusions This study provides evidence for causal effects of gut microbiota on menstruation quality of life impacts. These findings will help elucidate how gut microbiota could affect physiological and psychological health issues during menstruation. Furthermore, they also offer valuable perspectives into the management of women's health during menstruation.
IRIS: Iterative Improvement of Distantly Supervised Named Entity Annotations
Authors: Yano Ken , Miwa Makoto , Ananiadou Sophia 
Published: August 2024

Abstract

Background: Named entity recognition (NER) aims to detect entity mentions from text and classify them into predefined types. It is a fundamental task in information extraction and many other downstream tasks. However, the necessity of extensive human efforts to annotate a large amount of training data imposes restrictions on the state-of-the-art supervised deep learning methods, especially in specific domains. To address this problem, various distantly supervised methods (DS-NER), which aim to train NER models using automatically annotated training data based on external knowledge, such as dictionaries and knowledge bases, have been proposed. Although DS-NER methods are effective, the annotation quality tends to be noisy, which requires further manual checking and correction.
Methods: We propose a named entity annotation framework called IRIS (IteRative Improvement dS-ner).The IRIS framework is a client-server web application that aims to curate noisy named entity annotations made by DS-NERs initially annotated using only domain dictionaries. The tool provides a fast and efficient corpus search capability to correct annotation manually. Besides, a back-end offline process periodically launched to re-train the DS-NER by the updated annotations generates new annotations. The web tool provides a UI to compare current and new annotations, enabling curators to decide whether to replace old annotations with new ones. This curation process continues until the corpus quality converges.
Results: We adopt a simulation-based method using the BC5CDR dataset to evaluate the framework. The results show the effectiveness of our proposed annotation framework in reducing manual annotation or curation workload compared with manual annotation from scratch to obtain annotation results of similar quality.
Conclusions: Our proposed IRIS annotation framework introduces a novel approach, iteratively and semiautomatically correcting noisy entity annotations made by DS-NER. The results of the simulation-based experiments demonstrate that the IRIS framework significantly reduces human annotation efforts compared with naive manual annotation from scratch.
Combining Ability and Heterosis Studies for Yield Improvement in Rapeseed
Authors: Azim Jaber Bin , Chowdhury Noushin , Robin Arif Hasan Khan 
Published: August 2024

Abstract

Rapeseed (Brassica napus L.) is globally important for its edible oil. Breeders focus on enhancing favorable yield attributes to increase yield in this crop. A comprehensive 5 × 5 full-diallel study was conducted to explore gene action, combining ability, and heterosis for morphological characteristics, days to maturity, and yield traits in rapeseed. The findings revealed that these traits are influenced by additive and non-additive genetic factors, with non-additive effects particularly prominent. Therefore, delaying selection to later segregating generations may prove more effective. Significant reciprocal effects were observed across all traits indicating the role of maternal influence in trait expression. NAP-0721-1 and BD-10109 were identified as the top general combiners, while the F1 hybrids NAP-0724-2 × BD-7118 and BD-10109 × NAP-0724-2 were noted for favorable combinations related to days to maturity and plant height. For yield and yield attributes, BD-6951 × BD-7118, NAP-0721-1 × BD-10109, BD-7118 × NAP-0724-2, and BD-7118 × BD-6951 emerged as the most promising specific combiners. The study highlighted the potential of these genotypes to transfer important quantitative traits, with the cross-combination BD-6951 × BD-7118 demonstrating superior performance across multiple traits compared to its parental lines. These promising parent lines are recommended for use in breeding programs aimed at developing high-yielding rapeseed genotypes. At the same time the identified F1 hybrids can be utilized to select desirable segregates for further improvement of yield and related traits.
Detection of pathogenic Gram-negative bacteria using an antimicrobial peptides-modified bipolar electrode-electrochemiluminescence platform
Authors: Ji Lei , Wang Fengyang , Qi Yan , Qiao Fanglin , Xiong Xiaohui , Liu Yuanjian J. 
Published: August 2024

Abstract

Real-time, label-free detection of Gram-negative bacteria with high selectivity and sensitivity is demonstrated using a bipolar electrode-electrochemiluminescence (BPE-ECL) platform. This platform utilizes anode luminescence and cathode modification of antimicrobial peptides (AMPs) to effectively capture bacteria. Magainin I, basic AMP from Xenopus skin, boasting an a-helix structure, exhibits a preferential affinity for the surface of Gram-negative pathogens. The covalent attachment of the peptide's C-terminal carboxylic acid to the free amines of a previously thiolated linker ensures its secure immobilization onto the surface of interdigitated gold-plated cathode of BPE. The AMP-modified BPE sensor, when exposed to varying concentrations of Gram-negative bacteria, produces reproducible ECL intensities, allowing for the detection of peptide-bacteria interactions within the range of 1 to 104 CFU mL-1. Furthermore, this AMP-modified BPE sensor demonstrates a selective capacity to detect E. coli O157:H7 amidst other Gram-negative strains, even at a concentration of 1 CFU mL-1. This study underscores the high selectivity of Magainin I in bacterial detection, and the AMP-modified BPE-ECL system holds significant promise for rapid detection of Gram-negative bacteria in various applications. The AMP-modified BPE sensor to various concentrations of Gram-negative bacteria generated reproducible ECL intensity that detected peptide-bacteria interactions in the range of 1 to 104 CFU mL-1. The AMP-modified BPE sensor also selectively detected E. coli O157:H7 from other Gram-negative strains at a concentration of 1 CFU mL-1. In this paper, AMP demonstrated high selectivity in bacterial detection. The AMP-modified BPE-ECL system prepared has a great potential for application in the field of rapid detection of Gram-negative bacteria.
Functional Diversity Patterns in a Mountainous Mediterranean Refuge
Authors: Aykurt Candan , Özkan Kürşad , Gülben Mertcan , Şentürk Özdemir , Berberoğlu Emirhan , Türkan Semra , Öz Zeynep , Göktürk Ramazan Süleyman , Akgül Hasan , Günaydın Sinem , Görgöz Muhammet Murat 
Published: August 2024

Abstract

In this study, the variation in functional diversity along all Mediterranean-type vegetation belts in a topographically complex mountainous refuge area was examined in relation to topographic and climatic factors. Microclimatic processes and mosaic habitats caused by topographic complexity increase the plant diversity of the area. This diversity is reflected in our study through the representation of different habitat types, and all members of Spermatophyta in the sample plots were recorded. In addition to functional diversity, the relationship of alpha species diversity with enviromental parameters was also modeled and mapped within this study conducted with approximately 5550 records of 1017 plant taxa from 136 study plots. Functional diversity was measured using Rao’s quadratic entropy, and alpha species diversity values were calculated using the Shannon-Wiener index. Various regression models were trained and evaluated, and were assessed based on several statistical metrics. The final model selection, the Generalized Additive Model (GAM), was chosen based on its superior performance, ensuring the model not only fits the data well but also accurately predicts new data, thus optimizing both the validity and practical utility of the model. Our GAM results indicated that elevation is the most influential factor on diversity values, and that functional and species diversity curves show different trends with increasing elevation. Additionally, the topographic position index was identified as the most significant process affecting functional diversity in terms of “habitat filtering”. In this context, the variation in functional diversity, species diversity, and endemism in mosaic habitats creates a mosaic of diversity.
Effect of coincidence of severe extracranial and intracranial artery stenosis or occlusion on cerebral small vessel disease
Authors: Dai Pei , Fang Ya-na , Yu Hui-xian , Wang Zhao-xia , Liu Si-hao , Zang Da-wei 
Published: August 2024

Abstract

Objective: There was a significant correlation between the large atherosclerotic extracranial artery stenosis (ECAS) or intracranial artery stenosis (ICAS) and the neuroimaging markers of cerebral small vessel disease (CSVD). Our objective was to investigate the effect of coexistence of severe extracranial and intracranial arterial stenosis or occlusion on CSVD in patients with ischemic stroke.
Methods: A total of 222 patients with LAA infarction with CSVD were included in this retrospective study, including 160 males and 62 females. All enrolled patients were divided into four groups: ECAS, ECAS+ICAS, ICAS and None. The differences between the four groups were evaluated by total CSVD scores, total Fazekas scores, periventricular WMH Fazekas scores and deep WMH Fazekas scores.
Results: There were significant differences between the four groups in terms of total CSVD scores (P< 0.05). But there was no significant difference in the total Fazekas scores, periventricular WMH Fazekas scores and deep WMH Fazekas scores. Further pairwise comparison shows that only the ECAS+ICAS group and the none group had a significant difference in total CSVD scores (P < 0.05).
Conclusion: The coincidence of severe stenosis or occlusion of the extracranial and intracranial artery may increase the incidence of CSVD and aggravate the performance of CSVD in patients with ischemic stroke and mainly reflected in the total CSVD scores. If ECAS and/or ICAS are found in patients, the total CSVD burden should be also actively assessed. To reduce the incidence of stroke and improve outcomes, active clinical intervention should be undertaken for these patients.
An Experimental Database for Machine Learning of Algebraic Models in Separated Flows
Authors: Carlucci Andrea , Petronio Daniele , Dellacasagrande Matteo , Simoni Daniele , Satta Francesca 
Published: August 2024

Abstract

This work presents an extended experimental database characterizing the transition process induced by flow separation on a flat plate with a variable adverse pressure gradient, and demonstrates its usability for tuning algebraic models of the Reynolds stress tensor by means of machine learning techniques. The database collects the 2D components of the Reynolds stress tensor for about 90 flow cases characterized by different flow Reynolds numbers, freestream turbulence intensities and adverse pressure gradients. In the range of variation chosen for the aforementioned parameters, bursting process occurs, with the consequent formation of separation bubbles of both short and long types. Sparse Bayesian Learning has been exploited to tune two algebraic turbulence models, based on the Pope’s expansion, for short and long bubbles. The models have been formulated in terms of the invariants of the strain and rotation tensors with the addition of different physical-based flow features to account for the strong anisotropy that has been observed in the transitional region. The capability of the tuned relations in reproducing the anisotropy tensor along the separated shear layer is here shown by predicting flow cases that did not participate in the tuning process. The paper aims at providing a thorough database for future researches in the field and to improve turbulence models and RANS capabilities in the simulation of separated flows.
Single image dehazing method based on knowledge transfer and multi-branch data augmentation correction
Authors: Cao manman 
Published: August 2024

Abstract

Dehazing can improve the clarity of images and provide more reliable inputs for image analysis tasks, thereby enhancing their performance. Therefore, we propose a dehazing network based on knowledge transfer and multi-data enhancement correction. First, we propose a multi-data enhancement correction method that combines different image enhancement techniques to improve the quality of the input images. Second, by leveraging a pre-trained teacher network to acquire prior knowledge from clear data, guiding the dehazing process of the student network through knowledge transfer. We introduce a deep multi-scale refinement network composed of a dense feature enhancement module and enhanced residual dense blocks, enabling the dehazing model to learn the local structure and feature representation of the data more accurately. Experimental results on multiple benchmark datasets demonstrate that the proposed dehazing method outperforms state-of-the-art dehazing methods. Code are available at: https://github.com/JNcmm/KTMDA-DehazeNet.
Unequal roles of cities in the inter-urban healthcare system
Authors: Zhao Pengjun , Li Juan , Zhang Mengzhu 
Published: August 2024

Abstract

Cities are increasingly interdependent regarding healthcare provision/demand. However, the inter-urban healthcare system (IHS) behind the nationwide patient mobility remains largely unknown. Leveraging human mobility big data, we reveal cities’ roles in providing/demanding quality healthcare within the IHS of China. We find that 8%of Chinese cities arenational and regional hubs that address the healthcare shortage of cities deprived of quality healthcare, while 63% of the cities that are unnoticed compensate for migrant workers being denied healthcare rights in megacities. IHS generates new structural inequalities in healthcare access exhibiting a Matthew effect, where the few (12%) cities that are already rich in healthcare resources benefit more and can strengthen their advantages in providing healthcare to local populations (32% of China’s total population). While, the majority (35%) of cities, particularly those facing healthcare shortages, are further disadvantaged in ensuring adequate healthcare for their local populations (26% of China’s total population).
Inherited Genetic Risk in Stillbirth: A Shared Genomic Segments Analysis of High-Risk Pedigrees.
Authors: Workalemahu Tsegaselassie , Madsen Myke , Lopez Sarah , Page Jessica , Blue Nathan , Avery Cecile , Sargent Rob , Yu Zhe , Guinto Emily , Branch D Ware , Leisher Susannah , Jorde Lynn , Quinlan Aaron , Coon Hilary , Varner Michael , Roberts Claire , Neklason Deborah , Camp Nicola , Silver Robert 
Published: August 2024

Abstract

Background
Stillbirth is a devastating adverse pregnancy outcome affecting 2 million pregnancies worldwide every year. Though an etiology may be found in some, one-third of stillbirth cases remain unexplained. Stillbirth clusters in families and, apart from infrequent aneuploidies and balanced translocations, few underlying inherited genes associated with stillbirth are known. Well-characterized family-based studies may aid in identifying genetic contributors to unexplained stillbirth.
Methods
Using the Utah Population Database, we defined pedigrees with high familial risk of stillbirth. Comprehensive phenotyping with review of primary medical records was conducted to identify stillbirth cases without identifiable causes. We generated whole-genome sequencing in seven stillborn placentas from three pedigrees, referred to hereafter as Pedigree A, Pedigree B, and Pedigree C. We performed shared genomic segments analysis to identify evidence for segregating haplotypes shared by the stillbirths to provide evidence for inherited risk.
Results
A region at 15q26.3 was identified in two independent pedigrees with genome-wide significance in both (a 1.2 Mb segment shared by two stillbirths in Pedigree A, and a 1.8 Mb segment shared by two stillbirths in pedigree B). Four other regions reached genome-wide significance in single pedigrees at 16p13.13-p13.12, 9p13.3-p13.1, and 6p22.2-p22.1 (shared by the same two stillbirths in Pedigree B), and 0.8 Mb segment at 14q.32.2 shared by three stillbirths in Pedigree C. The identified regions are implicated in in utero and postnatal development, pregnancy loss, and infertility.
Conclusions
We identified evidence for inherited risk loci in stillbirth placental genes are implicated in in utero and postnatal development, pregnancy loss, and infertility. Identification of inherited genes in stillbirth risk may provide novel therapeutic targets for prevention and treatment to improve pregnancy outcomes.