bluuebunny/crossref_metadata_2025_split huggingface dataset:
A brain machine interface framework for exploring proactive control of smart environments
Authors: Braun Jan-Matthias , Fauth Michael , Berger Michael , Huang Nan-Sheng , Simeoni Ezequiel , Gaeta Eugenio , Rodrigues do Carmo Ricardo , García-Betances Rebeca I. , Arredondo Waldmeyer María Teresa , Gail Alexander , Larsen Jørgen C. , Manoonpong Poramate , Tetzlaff Christian , Wörgötter Florentin 
Published: May 2024

AbstractBrain machine interfaces (BMIs) can substantially improve the quality of life of elderly or disabled people. However, performing complex action sequences with a BMI system is onerous because it requires issuing commands sequentially. Fundamentally different from this, we have designed a BMI system that reads out mental planning activity and issues commands in a proactive manner. To demonstrate this, we recorded brain activity from freely-moving monkeys performing an instructed task and decoded it with an energy-efficient, small and mobile field-programmable gate array hardware decoder triggering real-time action execution on smart devices. Core of this is an adaptive decoding algorithm that can compensate for the day-by-day neuronal signal fluctuations with minimal re-calibration effort. We show that open-loop planning-ahead control is possible using signals from primary and pre-motor areas leading to significant time-gain in the execution of action sequences. This novel approach provides, thus, a stepping stone towards improved and more humane control of different smart environments with mobile brain machine interfaces.
Production study of Fr, Ra and Ac radioactive ion beams at ISOLDE, CERN
Authors: Jajčišinová E. , Dockx K. , Au M. , Bara S. , Cocolios T. E. , Chrysalidis K. , Farooq-Smith G. J. , Fedorov D. V. , Fedosseev V. N. , Flanagan K. T. , Heines M. , Houngbo D. , Johnson J. D. , Kellerbauer A. , Kraemer S. , Marsh B. A. , Popescu L. , Ramos J. P. , Rothe S. , Seliverstov M. D. , Sels S. , Stegemann S. , Stryjczyk M. , Verelst V. 
Published: May 2024

AbstractThe presented paper discusses the production of radioactive ion beams of francium, radium, and actinium from thick uranium carbide (UC$$_{x}$$

x

) targets at ISOLDE, CERN. This study focuses on the release curves and extractable yields of francium, radium and actinium isotopes. The ion source temperature was varied in order to study the relative contributions of surface and laser ionization to the production of the actinium ion beams. The experimental results are presented in the form of release parameters. Representative extractable yields per $$\mu$$
μ
C are presented for $$^{222-231}$$

222
-
231

Ac, several Ra and Fr isotopes in the mass ranges 214$$\le$$
≤
A$$\le$$
≤
233 and 205$$\le$$
≤
A$$\le$$
≤
231 respectively. The release efficiency for several isotopes of each of the studied elements was calculated by comparing their yields to the estimated in-target production rates modeled by CERN-FLUKA. The maximal extraction efficiency of actinium was calculated to be 2.1(6)% for a combination of surface ionization using a Ta ion source and resonant laser ionization using the two-step 438.58 nm, and 424.69 nm scheme.
Deep learning with diffusion MRI as in vivo microscope reveals sex-related differences in human white matter microstructure
Authors: Chen Junbo , Bayanagari Vara Lakshmi , Chung Sohae , Wang Yao , Lui Yvonne W. 
Published: May 2024

AbstractBiological sex is a crucial variable in neuroscience studies where sex differences have been documented across cognitive functions and neuropsychiatric disorders. While gross statistical differences have been previously documented in macroscopic brain structure such as cortical thickness or region size, less is understood about sex-related cellular-level microstructural differences which could provide insight into brain health and disease. Studying these microstructural differences between men and women paves the way for understanding brain disorders and diseases that manifest differently in different sexes. Diffusion MRI is an important in vivo, non-invasive methodology that provides a window into brain tissue microstructure. Our study develops multiple end-to-end classification models that accurately estimates the sex of a subject using volumetric diffusion MRI data and uses these models to identify white matter regions that differ the most between men and women. 471 male and 560 female healthy subjects (age range, 22–37 years) from the Human Connectome Project are included. Fractional anisotropy, mean diffusivity and mean kurtosis are used to capture brain tissue microstructure characteristics. Diffusion parametric maps are registered to a standard template to reduce bias that can arise from macroscopic anatomical differences like brain size and contour. This study employ three major model architectures: 2D convolutional neural networks, 3D convolutional neural networks and Vision Transformer (with self-supervised pretraining). Our results show that all 3 models achieve high sex classification performance (test AUC 0.92–0.98) across all diffusion metrics indicating definitive differences in white matter tissue microstructure between males and females. We further use complementary model architectures to inform about the pattern of detected microstructural differences and the influence of short-range versus long-range interactions. Occlusion analysis together with Wilcoxon signed-rank test is used to determine which white matter regions contribute most to sex classification. The results indicate that sex-related differences manifest in both local features as well as global features / longer-distance interactions of tissue microstructure. Our highly consistent findings across models provides new insight supporting differences between male and female brain cellular-level tissue organization particularly in the central white matter.
AI-based predictive approach via FFB propagation in a driven-cavity of Ostwald de-Waele fluid using CFD-ANN and Levenberg–Marquardt
Authors: Refaie Ali Ahmed , Mahmood Rashid , Asghar Atif , Majeed Afraz Hussain , Behiry Mohamed H. 
Published: May 2024

AbstractThe integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques into computational science has ushered in a new era of innovation and efficiency in various fields, with particular significance in computational fluid dynamics (CFD). Several methods based on AI and Machine Learning (ML) have been standardized in many fields of computational science, including computational fluid dynamics (CFD). This study aims to couple CFD with artificial neural networks (ANNs) to predict the fluid forces that arise when a flowing fluid interacts with obstacles installed in the flow domain. The momentum equation elucidating the flow has been simulated by adopting the finite element method (FEM) for a range of rheological and kinematic conditions. Hydrodynamic forces, including pressure drop between the back and front of the obstacle, surface drag, and lift variations, are measured on the outer surface of the cylinder via CFD simulations. This data has subsequently been fed into a Feed-Forward Back (FFB) propagation neural network for the prediction of such forces with completely unknown data. For all cases, higher predictivity is achieved for the drag coefficient (CD) and lift coefficient (CL) since the mean square error (MSE) is within ± 2% and the coefficient of determination (R) is approximately 99% for all the cases. The influence of pertinent parameters like the power law index (n) and Reynolds number (Re) on velocity, pressure, and drag and lift coefficients is also presented for limited cases. Moreover, a significant reduction in computing time has been noticed while applying hybrid CFD-ANN approach as compared with CFD simulations only.
Magnesium implantation as a continuous hydrogen production generator for the treatment of myocardial infarction in rats
Authors: Wang Bin , Pan Shuang , Nie Chaoqun , Zou Rentong , Liu Jiaren , Han Xue , Dong Li , Zhang Jiawen , Yang Xinrui , Yu Mengshu , Fan Bowei , Hong Xiaojian , Yang Wei 
Published: May 2024

AbstractMolecular hydrogen is an emerging broad-spectrum antioxidant molecule that can be used to treat myocardial infarction (MI). However, with hydrogen inhalation, the concentration that can be reached within target organs is low and the duration of action is short, which makes it difficult to achieve high dose targeted delivery of hydrogen to the heart, seriously limiting the therapeutic potential of hydrogen for MI. As a result of reactions with the internal environment of the body, subcutaneous implantation of magnesium slices leads to continuous endogenous hydrogen production, leading to a higher hydrogen concentration and a longer duration of action in target organs. In this study, we propose magnesium implant-based hydrogen therapy for MI. After subcutaneous implantation of magnesium slices in the dorsum of rats, we measured hydrogen production and efficiency, and evaluated the safety of this approach. Compared with hydrogen inhalation, it significantly improved cardiac function in rats with MI. Magnesium implantation also cleared free radicals that were released as a result of mitochondrial dysfunction, as well as suppressing cardiomyocyte apoptosis.
Mechanisms upholding the persistence of stigma across 100 years of historical text
Authors: Charlesworth Tessa E. S. , Hatzenbuehler Mark L. 
Published: May 2024

AbstractToday, many social groups face negative stereotypes. Is such negativity a stable feature of society and, if so, what mechanisms maintain stability both within and across group targets? Answering these theoretically and practically important questions requires data on dozens of group stereotypes examined simultaneously over historical and societal scales, which is only possible through recent advances in Natural Language Processing. Across two studies, we use word embeddings from millions of English-language books over 100 years (1900–2000) and extract stereotypes for 58 stigmatized groups. Study 1 examines aggregate, societal-level trends in stereotype negativity by averaging across these groups. Results reveal striking persistence in aggregate negativity (no meaningful slope), suggesting that society maintains a stable level of negative stereotypes. Study 2 introduces and tests a new framework identifying potential mechanisms upholding stereotype negativity over time. We find evidence of two key sources of this aggregate persistence: within-group “reproducibility” (e.g., stereotype negativity can be maintained by using different traits with the same underlying meaning) and across-group “replacement” (e.g., negativity from one group is transferred to other related groups). These findings provide novel historical evidence of mechanisms upholding stigmatization in society and raise new questions regarding the possibility of future stigma change.
Effect of weight loss program using prebiotics and probiotics on body composition, physique, and metabolic products: longitudinal intervention study
Authors: Hassan Nayera E. , El-Masry Sahar A. , El Shebini Salwa M. , Ahmed Nihad H. , Mehanna Nayra Sh. , Abdel Wahed Mai Magdy , Amine Darine , Hashish Adel , Selim Mohamed , Afify Mahmoud A. S. , Alian Khadija 
Published: May 2024

AbstractThe relationship between gut microbiota and obesity has recently been an important subject for research as the gut microbiota is thought to affect body homeostasis including body weight and composition, intervening with pro and prebiotics is an intelligent possible way for obesity management. To evaluate the effect of hypo caloric adequate fiber regimen with probiotic supplementation and physical exercise, whether it will have a good impact on health, body composition, and physique among obese Egyptian women or has no significant effect. The enrolled 58 women, in this longitudinal follow-up intervention study; followed a weight loss eating regimen (prebiotic), including a low-carbohydrate adequate-fiber adequate-protein dietary pattern with decreased energy intake. They additionally received daily probiotic supplements in the form of yogurt and were instructed to exercise regularly for 3 months. Anthropometric measurements, body composition, laboratory investigations, and microbiota analysis were obtained before and after the 3 months weight loss program. Statistically highly significant differences in the anthropometry, body composition parameters: and obesity-related biomarkers (Leptin, ALT, and AST) between the pre and post-follow-up measurements at the end of the study as they were all decreased. The prebiotic and probiotic supplementation induced statistically highly significant alterations in the composition of the gut microbiota with increased relative abundance of Lactobacillus, Bifidobacteria, and Bacteroidetes and decreased relative abundance of Firmicutes and Firmicutes/Bacteroidetes Ratio. Hypo caloric adequate fiber regimen diet with probiotics positively impacts body composition and is effective for weight loss normalizing serum Leptin and AST.
Quantitative microbiome profiling of honey bee (Apis mellifera) guts is predictive of winter colony loss in northern Virginia (USA)
Authors: Carlini David B. , Winslow Sundre K. , Cloppenborg-Schmidt Katja , Baines John F. 
Published: May 2024

AbstractFor the past 15 years, the proportion of honey bee hives that fail to survive winter has averaged ~ 30% in the United States. Winter hive loss has significant negative impacts on agriculture, the economy, and ecosystems. Compared to other factors, the role of honey bee gut microbial communities in driving winter hive loss has received little attention. We investigate the relationship between winter survival and honey bee gut microbiome composition of 168 honey bees from 23 hives, nine of which failed to survive through winter 2022. We found that there was a substantial difference in the abundance and community composition of honey bee gut microbiomes based on hive condition, i.e., winter survival or failure. The overall microbial abundance, as assessed using Quantitative Microbiome Profiling (QMP), was significantly greater in hives that survived winter 2022 than in those that failed, and the average overall abundance of each of ten bacterial genera was also greater in surviving hives. There were no significant differences in alpha diversity based on hive condition, but there was a highly significant difference in beta diversity. The bacterial genera Commensalibacter and Snodgrassella were positively associated with winter hive survival. Logistic regression and random forest machine learning models on pooled ASV counts for the genus data were highly predictive of winter outcome, although model performance decreased when samples from the location with no hive failures were excluded from analysis. As a whole, our results show that the abundance and community composition of honey bee gut microbiota is associated with winter hive loss, and can potentially be used as a diagnostic tool in evaluating hive health prior to the onset of winter. Future work on the functional characterization of the honey bee gut microbiome’s role in winter survival is warranted.
Cryptic diversity in southern African kelp
Authors: Madeira Pedro , Reddy Maggie M. , Assis Jorge , Bolton John J. , Rothman Mark D. , Anderson Robert J. , Kandjengo Lineekela , Kreiner Anja , Coleman Melinda A. , Wernberg Thomas , De Clerck Olivier , Leliaert Frederik , Bandeira Salomão , Ada Abdul M. , Neiva João , Pearson Gareth A. , Serrão Ester A. 
Published: May 2024

AbstractThe southern coast of Africa is one of the few places in the world where water temperatures are predicted to cool in the future. This endemism-rich coastline is home to two sister species of kelps of the genus Ecklonia maxima and Ecklonia radiata, each associated with specific thermal niches, and occuring primarily on opposite sides of the southern tip of Africa. Historical distribution records indicate that E. maxima has recently shifted its distribution ~ 70 km eastward, to sites where only E. radiata was previously reported. The contact of sister species with contrasting thermal affinities and the occurrence of mixed morphologies raised the hypothesis that hybridization might be occurring in this contact zone. Here we describe the genetic structure of the genus Ecklonia along the southern coast of Africa and investigate potential hybridization and cryptic diversity using a combination of nuclear microsatellites and mitochondrial markers. We found that both species have geographically discrete genetic clusters, consistent with expected phylogeographic breaks along this coastline. In addition, depth-isolated populations were found to harbor unique genetic diversity, including a third Ecklonia lineage. Mito-nuclear discordance and high genetic divergence in the contact zones suggest multiple hybridization events between Ecklonia species. Discordance between morphological and molecular identification suggests the potential influence of abiotic factors leading to convergent phenotypes in the contact zones. Our results highlight an example of cryptic diversity and hybridization driven by contact between two closely related keystone species with contrasting thermal affinities.
Inducible deletion of microRNA activity in kidney mesenchymal cells exacerbates renal fibrosis
Authors: Sakuma Hirofumi , Maruyama Keisuke , Aonuma Tatsuya , Kobayashi Yuya , Hayasaka Taiki , Kano Kohei , Kawaguchi Satoshi , Nakajima Kei-ichi , Kawabe Jun-ichi , Hasebe Naoyuki , Nakagawa Naoki 
Published: May 2024

AbstractMicroRNAs (miRNAs) are sequence-specific inhibitors of post-transcriptional gene expression. However, the physiological functions of these non-coding RNAs in renal interstitial mesenchymal cells remain unclear. To conclusively evaluate the role of miRNAs, we generated conditional knockout (cKO) mice with platelet-derived growth factor receptor-β (PDGFR-β)-specific inactivation of the key miRNA pathway gene Dicer. The cKO mice were subjected to unilateral ureteral ligation, and renal interstitial fibrosis was quantitatively evaluated using real-time polymerase chain reaction and immunofluorescence staining. Compared with control mice, cKO mice had exacerbated interstitial fibrosis exhibited by immunofluorescence staining and mRNA expression of PDGFR-β. A microarray analysis showed decreased expressions of miR-9-5p, miR-344g-3p, and miR-7074-3p in cKO mice compared with those in control mice, suggesting an association with the increased expression of PDGFR-β. An analysis of the signaling pathways showed that the major transcriptional changes in cKO mice were related to smooth muscle cell differentiation, regulation of DNA metabolic processes and the actin cytoskeleton, positive regulation of fibroblast proliferation and Ras protein signal transduction, and focal adhesion-PI3K/Akt/mTOR signaling pathways. Depletion of Dicer in mesenchymal cells may downregulate the signaling pathway related to miR-9-5p, miR-344g-3p, and miR-7074-3p, which can lead to the progression of chronic kidney disease. These findings highlight the possibility for future diagnostic or therapeutic developments for renal fibrosis using miR-9-5p, miR-344g-3p, and miR-7074-3p.
Supplemental structured surveys and pre-existing detection models improve fine-scale density and population estimation with opportunistic community science data
Authors: Hallman Tyler A. , Robinson W. Douglas 
Published: May 2024

AbstractDensity and population estimates aid in conservation and stakeholder communication. While free and broadly available community science data can effectively inform species distribution models, they often lack the information necessary to estimate imperfect detection and area sampled, thus limiting their use in fine-scale density modeling. We used structured distance-sampling surveys to model detection probability and calculate survey-specific detection offsets in community science models. We estimated density and population for 16 songbird species under three frameworks: (1) a fixed framework that assumes perfect detection within a specified survey radius, (2) an independent framework that calculates offsets from an independent source, and (3) a calibration framework that calculates offsets from supplemental surveys. Within the calibration framework, we examined the effects of calibration dataset size and data pooling. Estimates of density and population size were consistently biased low in the fixed framework. The independent and calibration frameworks produced reliable estimates for some species, but biased estimates for others, indicating discrepancies in detection probability between structured and community science surveys. The calibration framework produced reliable population estimates with as few as 10 calibration surveys with positive detections. Data pooling dramatically decreased bias. This study provides conservationists and managers with a cost-effective method of estimating density and population.
Major chromosome rearrangements in intergeneric wheat × rye hybrids in compatible and incompatible crosses detected by GBS read coverage analysis
Authors: Tikhenko Natalia , Haupt Max , Fuchs Jörg , Perovic Dragan , Himmelbach Axel , Mascher Martin , Houben Andreas , Rutten Twan , Nagel Manuela , Tsvetkova Natalia V. , Sehmisch Stefanie , Börner Andreas 
Published: May 2024

AbstractThe presence of incompatibility alleles in primary amphidiploids constitutes a reproductive barrier in newly synthesized wheat-rye hybrids. To overcome this barrier, the genome stabilization process includes large-scale chromosome rearrangements. In incompatible crosses resulting in fertile amphidiploids, the elimination of one of the incompatible alleles Eml-A1 or Eml-R1b can occur already in the somatic tissue of the wheat × rye hybrid embryo. We observed that the interaction of incompatible loci Eml-A1 of wheat and Eml-R1b of rye after overcoming embryo lethality leads to hybrid sterility in primary triticale. During subsequent seed reproductions (R1, R2 or R3) most of the chromosomes of A, B, D and R subgenomes undergo rearrangement or eliminations to increase the fertility of the amphidiploid by natural selection. Genotyping-by-sequencing (GBS) coverage analysis showed that improved fertility is associated with the elimination of entire and partial chromosomes carrying factors that either cause the disruption of plant development in hybrid plants or lead to the restoration of the euploid number of chromosomes (2n = 56) in the absence of one of the incompatible alleles. Highly fertile offspring obtained in compatible and incompatible crosses can be successfully adapted for the production of triticale pre-breeding stocks.
First insights into the age of the giant ice deposits in the Eisriesenwelt cave (Austria)
Authors: Spötl Christoph , Fohlmeister Jens , Reimer Paula , Zhang Haiwei 
Published: May 2024

AbstractFrozen water is the most widespread type of ice present in ice caves and forms ice stalagmites and stalactites as well as floor ice, which is often several meters thick. Organic macroremains are commonly rare in this type of cave ice, which makes it difficult to establish a chronology and severely limits the use of such ice deposits as paleoenvironmental archives. Here, the chronology of such ice deposits in the inner part of the glaciated Eisriesenwelt, one of the world’s largest ice caves located in the European Alps of Austria, is determined by a combination of radiocarbon and 230Th dating of cryogenic calcite. The data suggest that this cave ice has formed over the last three millennia, with a marked increase in the average accumulation rate during the thirteenth century, coinciding with the onset of the Little Ice Age in the Alps. Data from a second site closer to the entrance suggests that large parts of this tourist cave were likely ice-free during the Medieval Warm Period and that a substantial part of the ice is probably a relic of the Little Ice Age. The current warming has already penetrated deeper into the cave than during the Medieval Warm Period, although air exchange during the warm season is restricted by a door at the cave entrance.