bluuebunny/crossref_metadata_2025_split huggingface dataset:
Acute inorganic nitrate ingestion does not impact oral microbial composition, cognitive function, or high-intensity exercise performance in female team-sport athletes
Authors: Tan Rachel , Merrill Courtney , Riley Chandler F. , Hammer Maya A. , Kenney Ryan T. , Riley Alyssa A. , Li Jeffrey , Zink Alexandra C. , Karl Sean T. , Price Katherine M. , Sharabidze Luka K. , Rowland Samantha N. , Bailey Stephen J. , Stiemsma Leah T. , Pennell Adam 
Published: July 2024

AbstractThe purpose of this study was to investigate the effects of acute nitrate (NO3−)-rich beetroot juice ingestion on explosive and high-intensity exercise performance, oral microbiota composition, and cognitive flexibility (i.e., function), before and after maximal intermittent running exercise. Fifteen women team-sport athletes were assigned in a randomized, double-blind, crossover design to consume concentrated NO3–-depleted beetroot juice (PL; 0.1 mmol NO3−) and NO3−-rich beetroot juice (BR; 12.0 mmol NO3−) 2.5 h prior to performing a battery of exercise performance tasks and cognitive testing before and after the Yo–Yo intermittent recovery level 1 (YYIR1) running test. Resting plasma [NO3−] and plasma nitrite ([NO2−]) were elevated following BR (P < 0.001). BR did not impact global composition or relative abundance of taxa in the oral microbiome (P > 0.05) or cognitive flexibility before or after exercise (P > 0.05). There was no significant difference in performance during 20-m (PRE, PL: 4.38 ± 0.27 vs. BR: 4.38 ± 0.32 s; POST, PL: 4.45 ± 0.29 vs. BR: 4.43 ± 0.35 s) and 10-m sprints (PRE, PL 2.78 ± 0.15 vs. BR 2.79 ± 0.18 s; POST, PL: 2.82 ± 0.16 vs. BR: 2.81 ± 0.19 s), isokinetic handgrip dynamometry, medicine ball throw, horizontal countermovement jump, or YYIR1 (PL: 355 ± 163 m vs. BR: 368 ± 184 m) between BR and PL (P > 0.05). These findings indicate that acute dietary NO3− may not influence the oral microbiome, explosive and high-intensity exercise performance, or cognitive function in women team-sport athletes.
A preliminary study of white matter disconnections underlying deficits in praxis in left hemisphere stroke patients
Authors: Rounis Elisabeth , Thompson Elinor , Scandola Michele , Nozais Victor , Pizzamiglio Gloria , de Schotten Michel Thiebaut , Pacella Valentina 
Published: July 2024

AbstractLimb apraxia is a higher-order motor disorder often occurring post-stroke, which affects skilled actions. It is assessed through tasks involving gesture production or pantomime, recognition, meaningless gesture imitation, complex figure drawing, single and multi-object use. A two-system model for the organisation of actions hypothesizes distinct pathways mediating praxis deficits via conceptual, ‘indirect’, and perceptual ‘direct’ routes to action. Traditional lesion- symptom mapping techniques have failed to identify these distinct routes. We assessed 29 left hemisphere stroke patients to investigate white matter disconnections on deficits of praxis tasks from the Birmingham Cognitive Screening. White matter disconnection maps derived from patients’ structural T1 lesions were created using a diffusion-weighted healthy participant dataset acquired from the human connectome project (HCP). Initial group-level regression analyses revealed significant disconnection between occipital lobes via the splenium of the corpus callosum and involvement of the inferior longitudinal fasciculus in meaningless gesture imitation deficits. There was a trend of left fornix disconnection in gesture production deficits. Further, voxel-wise Bayesian Crawford single-case analyses performed on two patients with the most severe meaningless gesture imitation and meaningful gesture production deficits, respectively, confirmed distinct posterior interhemispheric disconnection, for the former, and disconnections between temporal and frontal areas via the fornix, rostrum of the corpus callosum and anterior cingulum, for the latter. Our results suggest distinct pathways associated with perceptual and conceptual deficits akin to ‘direct’ and ‘indirect’ action routes, with some patients displaying both. Larger studies are needed to validate and elaborate on these findings, advancing our understanding of limb apraxia.
Comparative analysis of the chimpanzee and human brain superficial structural connectivities
Authors: Chauvel Maëlig , Pascucci Marco , Uszynski Ivy , Herlin Bastien , Mangin Jean-François , Hopkins William D. , Poupon Cyril 
Published: July 2024

AbstractDiffusion MRI tractography (dMRI) has fundamentally transformed our ability to investigate white matter pathways in the human brain. While long-range connections have extensively been studied, superficial white matter bundles (SWMBs) have remained a relatively underexplored aspect of brain connectivity. This study undertakes a comprehensive examination of SWMB connectivity in both the human and chimpanzee brains, employing a novel combination of empirical and geometric methodologies to classify SWMB morphology in an objective manner. Leveraging two anatomical atlases, the Ginkgo Chauvel chimpanzee atlas and the Ginkgo Chauvel human atlas, comprising respectively 844 and 1375 superficial bundles, this research focuses on sparse representations of the morphology of SWMBs to explore the little-understood superficial connectivity of the chimpanzee brain and facilitate a deeper understanding of the variability in shape of these bundles. While similar, already well-known in human U-shape fibers were observed in both species, other shapes with more complex geometry such as 6 and J shapes were encountered. The localisation of the different bundle morphologies, putatively reflecting the brain gyrification process, was different between humans and chimpanzees using an isomap-based shape analysis approach. Ultimately, the analysis aims to uncover both commonalities and disparities in SWMBs between chimpanzees and humans, shedding light on the evolution and organization of these crucial neural structures.
Molecular identification and morphological variations of Amblyomma lepidum imported to Egypt, with notes about its potential distribution under climate change
Authors: Abouelhassan Eman M. , GadAllah Sohair , Kamel Marwa S. , Kamal Mahmoud , Elsayed Hazem H. , Sallam Nahla H. , Okely Mohammed 
Published: July 2024

AbstractThe tick Amblyomma lepidum is an ectoparasite of veterinary importance due to its role in transmitting livestock diseases in Africa, including heartwater. This study was conducted in 2023 to monitor Amblyomma spp. infestation in dromedary camels imported from Somalia, Ethiopia, and Sudan to Egypt. This study inspected 200 camels at the Giza governorate’s camel market that had been imported from Somalia, 200 from Ethiopia, and 200 from Sudan for tick infestation. Specimens were identified using morphological characteristics and phylogenetic analyses of the 12S and 16S rRNA genes. Clusters were calculated using an unweighted pair-group method with arithmetic averages (UPGMA) dendrogram to group the specimens according to their morphometric characteristics. The morphometric analysis compared the body shape of ticks collected from different countries by analyzing dorsal features. Principal component analysis (PCA) and canonical variate analysis (CVA) were performed to obtain body shape variation among specimens from different countries. Results indicated that camels were infested by 57 males Amblyomma lepidum, and no female specimens were observed; among these specimens, one may have a morphological abnormality. The results suggest that A. lepidum specimens collected from camels imported to Egypt from African countries exhibit locally adapted morphology with variations among specimens, particularly variations in body size. This adaptation suggests minimal potential for genetic divergence. Ecological niche modeling was used to predict the areas in Africa with suitable climates for A. lepidum. The study confirmed that East African countries might have the most favorable climatic conditions for A. lepidum to thrive. Interestingly, the amount of rain during the wettest quarter (Bio16) had the strongest influence on the tick’s potential distribution, with suitability decreasing sharply as rainfall increased. Future predictions indicate that the climatic habitat suitability for A. lepidum will decrease under changing climate conditions. However, historical, current, and future predictions indicate no suitable climatic habitats for A. lepidum in Egypt. These findings demand continuous surveillance of A. lepidum in camel populations and the development of targeted strategies to manage tick infestations and prevent the spread of heartwater disease.
The relation of osteoporotic vertebral fractures and spine degeneration on the occurrence of complications: a systematic review
Authors: Wiersbicki Dina W. , Osterhoff Georg , Heyde Christoph-E , Pieroh Philipp 
Published: July 2024

Abstract
Study design
Systematic review.

Purpose
Osteoporotic vertebral fractures (OVFs) and degenerative spine conditions are age-related and associated with higher morbidity and mortality and greater health care costs. The relationship between OVFs and prevalent spine degeneration is rarely reported. The aim of this study was to systematically review current literature on the influence of preexisting degenerative spine conditions in patients with OVFs on the occurrence of complications during and after treatment.

Methods
A systematic literature review adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was performed using Web of Science and MEDLINE. We considered English and German articles published from January 1990 to December 2022. The inclusion criteria were patients with OVFs and preexisting spinal degeneration with complications such as subsequent fractures, deformity, implant failure and surgical and general complications. The included studies were controlled trials, cohort studies, and case series.

Results
Ten articles met the inclusion criteria (two prospective studies, seven retrospective studies and one case series). These were divided into two groups: studies on OVFs in patients with coexisting degenerative spine conditions (n = 5) and studies on OVFs following surgical treatment for degenerative spine conditions (n = 5). Three studies reported more complications in patients with OVFs and severe degeneration. One study stated the opposite. One study did not find any correlation. The remaining studies described complications narratively. Subsequent fractures were the most frequent complications.

Conclusion
OVFs in patients with preexisting spinal degeneration seem to cause more complications. In addition to subsequent fractures, other complications have rarely been examined. The presence of degenerative changes or undergoing surgical correction may increase the risk of subsequent fractures.
Formal education as a contested pastoral adaptation pathway: insights from southern Kenya
Authors: Marty Edwige 
Published: July 2024

AbstractIn dryland pastoral environments, political and geographical marginalization has historically led to development strategies that poorly account for individual and communities’ spatial and socio-economic realities. These development legacies, including long-standing epistemic biases in defining what should be adapted, are often insufficiently considered within adaptation research and practice. This article sets out to analyze the historical emergence and enactment of formal education as a contested adaptation pathway in southern Kenya. For this, I combine the strengths of the historically situated analyses of the pathways scholarship and feminist political ecology’s attention to the performance of intersectional relations of power in everyday livelihood practices. I bring together both archival data and qualitative primary data from focus group discussions (n = 16) and individual interviews (n = 122) conducted in three pastoral communities. The results exemplify the ways that non-climatic factors, such as increased formal school enrolment, (re)shape everyday livelihood practices and social aspirations, molding the current adaptation space. Notably, enacting formal education as an adaptation pathway requires one to navigate increasing cash pressures, mobility, and labor constraints. Wealth disparities, gendered norms, and geographies intersect to shape patterns of vulnerability, with poorer pastoralists residing further away from school centers facing difficult trade-offs on their time and resources. Understanding pathways enactments contributes to problematizing current logics of development and adaptation needs, while yielding important information on socio-spatial differentiation processes in pastoral systems. It also opens the space for further research to use these critical insights to identify alternative adaptation pathways that support more just transformations towards sustainability.
Robust anomaly detection via adversarial counterfactual generation
Authors: Liguori Angelica , Ritacco Ettore , Pisani Francesco Sergio , Manco Giuseppe 
Published: July 2024

AbstractThe capability to devise robust outlier and anomaly detection tools is an important research topic in machine learning and data mining. Recent techniques have been focusing on reinforcing detection with sophisticated data generation tools that successfully refine the learning process by generating variants of the data that expand the recognition capabilities of the outlier detector. In this paper, we propose $$\textrm{ARN}$$
ARN
, a semi-supervised anomaly detection and generation method based on adversarial counterfactual reconstruction. $$\textrm{ARN}$$
ARN
exploits a regularized autoencoder to optimize the reconstruction of variants of normal examples with minimal differences that are recognized as outliers. The combination of regularization and counterfactual reconstruction helps to stabilize the learning process, which results in both realistic outlier generation and substantially extended detection capability. In fact, the counterfactual generation enables a smart exploration of the search space by successfully relating small changes in all the actual samples from the true distribution to high anomaly scores. Experiments on several benchmark datasets show that our model improves the current state of the art by valuable margins because of its ability to model the true boundaries of the data manifold.
Archetypes of blockchain-based business models in enterprise networks
Authors: Grünewald Alexander , Gürpinar Tan , Culotta Carina , Guderian Alicia 
Published: July 2024

AbstractMany enterprises are currently engaged in developing blockchain-based business models. Enterprise networks offer a variety of potential applications for blockchain solutions as they benefit from transparency and security as well as automation of handling data, material, and financial flows along their supply chains. Despite profound potentials, the indicated business models are still in their early stages and need further investigation. To provide an overview of existing blockchain-based business models in the context of enterprise networks, the underlying paper designs a multidimensional taxonomy and identifies several archetypes of blockchain-based businesses. For the taxonomy development, data from 101 blockchain start-ups serves as a basis for empirical validation. Using hierarchical clustering and the k-means method, seven archetypes that sharpen the understanding of how blockchain solutions affect business models in enterprise networks and enable new business models are derived. The proposed work results are intended to be applied in future research and practice to classify and assess the integration of blockchain solutions into existing business models and to support developing new ones that leverage emerging technological capabilities.
Enhanced Domain Adaptation for Foot Ulcer Segmentation Through Mixing Self-Trained Weak Labels
Authors: Hresko David Jozef , Drotar Peter , Ngo Quoc Cuong , Kumar Dinesh Kant 
Published: July 2024

Abstract
Wound management requires the measurement of the wound parameters such as its shape and area. However, computerized analysis of the wound suffers the challenge of inexact segmentation of the wound images due to limited or inaccurate labels. It is a common scenario that the source domain provides an abundance of labeled data, while the target domain provides only limited labels. To overcome this, we propose a novel approach that combines self-training learning and mixup augmentation. The neural network is trained on the source domain to generate weak labels on the target domain via the self-training process. In the second stage, generated labels are mixed up with labels from the source domain to retrain the neural network and enhance generalization across diverse datasets. The efficacy of our approach was evaluated using the DFUC 2022, FUSeg, and RMIT datasets, demonstrating substantial improvements in segmentation accuracy and robustness across different data distributions. Specifically, in single-domain experiments, segmentation on the DFUC 2022 dataset scored a dice score of 0.711, while the score on the FUSeg dataset achieved 0.859. For domain adaptation, when these datasets were used as target datasets, the dice scores were 0.714 for DFUC 2022 and 0.561 for FUSeg.
Syndemic Psychosocial Conditions among Youth Living with HIV: a Latent Class Analysis
Authors: Wiginton John Mark , Amico K. Rivet , Hightow-Weidman Lisa , Sullivan Patrick , Horvath Keith J. 
Published: July 2024

AbstractDrug use, mental distress, and other psychosocial factors threaten HIV care for youth living with HIV (YLWH). We aimed to identify syndemic psychosocial patterns among YLWH and examine how such patterns shape HIV outcomes. Using baseline data from 208 YLWH enrolled in an HIV treatment adherence intervention, we performed latent class analysis on dichotomized responses to 9 psychosocial indicators (enacted HIV stigma; clinical depression and anxiety; alcohol, marijuana, and illicit drug misuse; food and housing insecurity; legal history). We used multinomial logistic regression to assess latent class-demographic associations and the automatic Bolck-Croon-Hagenaars method to assess HIV outcomes by class. Mean age of participants was 21 years; two thirds identified as cis male, 60% were non-Hispanic Black, and half identified as gay. Three classes emerged: “Polydrug-Socioeconomic Syndemic” (n = 29; 13.9%), “Distress-Socioeconomic Syndemic” (n = 35, 17.1%), and “Syndemic-free” (n = 142, 69.0%). Older, unemployed non-students were overrepresented in the “Polydrug-Socioeconomic Syndemic” class. Missed/no HIV care appointments was significantly higher in the “Polydrug-Socioeconomic Syndemic” class (81.4%) relative to the “Syndemic-free” (32.8%) and “Distress-Socioeconomic Syndemic” (31.0%) classes. HIV treatment nonadherence was significantly higher in the “Polydrug-Socioeconomic Syndemic” class (88.5%) relative to the “Syndemic-free” class (59.4%) but not the “Distress-Socioeconomic Syndemic” class (70.8%). Lack of HIV viral load suppression was non-significantly higher in the “Polydrug-Socioeconomic Syndemic” class (29.7%) relative to the “Syndemic-free” (16.2%) and “Distress-Socioeconomic Syndemic” (15.4%) classes. Polydrug-using, socioeconomically vulnerable YLWH are at risk for adverse HIV outcomes, warranting tailored programming integrated into extant systems of HIV care.
Approximate dynamic programming for liner shipping network design
Authors: Lee Sangmin , Boomsma Trine Krogh , Holst Klaus Kähler 
Published: July 2024

AbstractThe global containerised trade heavily relies on liner shipping services, facilitating the worldwide movement of large cargo volumes along fixed routes and schedules. The profitability of shipping companies hinges on how efficiently they design their shipping network; a complex optimization problem known as the liner shipping network design problem (LSNDP). In recent years, approximate dynamic programming (ADP), also known as reinforcement learning, has emerged as a promising approach for large-scale optimisation. This paper introduces a novel Markov decision process for the LSNDP and investigates the potential of ADP. We show that ADP methods based on value iteration produce optimal solutions to small instances, but their scalability is hindered by high memory demands. An ADP method based on a deep neural network requires less memory and successfully obtains feasible solutions. The quality of solutions, however, declines for larger instances, possibly due to the discrete nature of high-dimensional state and action spaces.
A Comparison of Evaluation Methodologies of the Fractal Dimension of Premixed Turbulent Flames in 2D and 3D Using Direct Numerical Simulation Data
Authors: Herbert Marco , Chakraborty Nilanjan , Klein Markus 
Published: July 2024

AbstractA Direct Numerical Simulation (DNS) database of statistically planar flames ranging from the wrinkled flamelets to the thin reaction zones regime and DNS data for a Bunsen premixed flame representing the wrinkled flamelets regime have been utilised to evaluate the fractal dimensions of flame surfaces using the filtering dimension method, the box-counting algorithm and the correlation dimension approach. The fractal dimension evaluated based on the fully resolved three-dimensional data has been found to be reasonably approximated by adding unity to the equivalent fractal dimension evaluated based on two-dimensional projections irrespective of the methodology of extracting fractal dimension. This indicates that the flame surface can be approximated as a self-similar fractal surface for the range of Karlovitz and Damköhler numbers considered here. While all methods, provide results identical to each other for benchmark problems, it has been found that the fractal dimension evaluation based on box-counting method provides almost identical results as that obtained using the filtering dimension method for both three and two dimensions, while the fractal dimensions based on the correlation dimension tend to be slightly smaller. The findings of the current analysis have the potential to be used to reliably estimate the actual fractal dimension in 3D based on experimentally obtained 2D binarised reaction progress variable field. The inner cut-off scales estimated based on all three methodologies yield comparable results in terms of order of magnitude with the box-counting method predicting a smaller value of inner cut-off scale in comparison to other methods. The execution times for fractal dimension extraction based on filtering dimension and box-counting methodologies are found to be comparable but the correlation dimension method is found to be considerably faster than the two alternative approaches and provides results consistent with theoretical bounds in all cases.