bluuebunny/crossref_metadata_2025_split huggingface dataset:
Image analysis and teaching strategy optimization of folk dance training based on the deep neural network
Authors: Li Zhou 
Published: May 2024

AbstractTo improve the recognition effect of the folk dance image recognition model and put forward new suggestions for teachers’ teaching strategies, this study introduces a Deep Neural Network (DNN) to optimize the folk dance training image recognition model. Moreover, a corresponding teaching strategy optimization scheme is proposed according to the experimental results. Firstly, the image preprocessing and feature extraction of DNN are optimized. Secondly, classification and target detection models are established to analyze the folk dance training images, and the C-dance dataset is used for experiments. Finally, the results are compared with those of the Naive Bayes classifier, K-nearest neighbor, decision tree classifier, support vector machine, and logistic regression models. The results of this study provide new suggestions for teaching strategies. The research results indicate that the optimized classification model shows a significant improvement in classification accuracy across various aspects such as action complexity, dance types, movement speed, dance styles, body dynamics, and rhythm. The accuracy, precision, recall, and F1 scores have increased by approximately 14.7, 11.8, 13.2, and 17.4%, respectively. In the study of factors such as different training images, changes in perspective, lighting conditions, and noise interference, the optimized model demonstrates a substantial enhancement in recognition accuracy and robustness. These findings suggest that, compared to traditional models, the optimized model performs better in identifying various dances and movements, enhancing the accuracy and stability of classification. Based on the experimental results, strategies for optimizing the real-time feedback and assessment mechanism in folk dance teaching, as well as the design of personalized learning paths, are proposed. Therefore, this study holds the potential to be applied in the field of folk dance, promoting the development and innovation of folk dance education.
Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology
Authors: Zhang Shufan , Wu Yue , Skaro Michael , Cheong Jia-Hwei , Bouffier-Landrum Amanda , Torrres Isaac , Guo Yinping , Stupp Lauren , Lincoln Brooke , Prestel Anna , Felt Camryn , Spann Sedona , Mandal Abhyuday , Johnson Nancy , Arnold Jonathan 
Published: May 2024

AbstractThe presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum. The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.
Suppression of the TGF-β signaling exacerbates degeneration of auditory neurons in kanamycin-induced ototoxicity in mice
Authors: Nitta Yoshihiro , Kurioka Takaomi , Mogi Sachiyo , Sano Hajime , Yamashita Taku 
Published: May 2024

AbstractTransforming growth factor-β (TGF-β) signaling plays a significant role in multiple biological processes, including inflammation, immunity, and cell death. However, its specific impact on the cochlea remains unclear. In this study, we aimed to investigate the effects of TGF-β signaling suppression on auditory function and cochlear pathology in mice with kanamycin-induced ototoxicity. Kanamycin and furosemide (KM-FS) were systemically administered to 8-week-old C57/BL6 mice, followed by immediate topical application of a TGF-β receptor inhibitor (TGF-βRI) onto the round window membrane. Results showed significant TGF-β receptor upregulation in spiral ganglion neurons (SGNs) after KM-FA ototoxicity, whereas expression levels in the TGF-βRI treated group remained unchanged. Interestingly, despite no significant change in cochlear TGF-β expression after KM-FS ototoxicity, TGF-βRI treatment resulted in a significant decrease in TGF-β signaling. Regarding auditory function, TGF-βRI treatment offered no therapeutic effects on hearing thresholds and hair cell survival following KM-FS ototoxicity. However, SGN loss and macrophage infiltration were significantly increased with TGF-βRI treatment. These results imply that inhibition of TGF-β signaling after KM-FS ototoxicity promotes cochlear inflammation and SGN degeneration.
Pulsed radio wave as a sustainable control technology to improve indoor air quality
Authors: Undi G. S. N. V. K. S. N. Swamy , Ramya Cheramangalath Balan , Sola Srikanth , Kanniganti Radhica , Shinde Kiran 
Published: May 2024

AbstractThe need for technologies that can clean the air indoors has grown in pace with the rise in outside pollution. Maintaining interior environment adaptability requires a permanent air purification system that may be utilized to control PM2.5/10. In addition to more traditional methods of air purification, developing advanced control systems that effectively reduce PM levels sustainably is necessary. Pulsed radio waves may expedite the dry deposition of particles having aerodynamic dimensions of less than 30 µm. The charging and coagulation processes are evaluated in an indoor restricted environment. Experimental results reveal a similar pattern to the Monte Carlo models. Distribution of charge due to the nature of the charging environment increases the coagulation rate. Contained experimental testing confirms the filtering system functions as expected, corroborated by the present research. Daily average levels of PM2.5 and PM10 were lowered by between 55 and 41% according to a study done in three indoor settings using the control technology. Research conducted throughout all seasons showed that the approach was consistently efficient in reducing PM2.5/10. It was shown that PM concentrations could be lowered by around 45 percent using pulse radio wave technology, leading to this conclusion. The use of electromagnetic waves (EM waves) to eliminate air pollution has been suggested as a radical new approach. Considering the limitations of already used strategies, this is of paramount significance while considering solutions to control air pollution.
Long range transport of South and East Asian anthropogenic aerosols counteracting Arctic warming
Authors: Fadnavis Suvarna , Sonbawne Sunil M. , Laakso Anton , Ploeger Felix , Rap Alexandru , Heinold Bernd , Sabin T. P. , Müller Rolf 
Published: May 2024

AbstractThe large-scale convection during the Asian summer monsoon plays an important role in the rapid transport of boundary layer aerosols into the Asian summer monsoon anticyclone. Here, using the state-of-the-art ECHAM6–HAMMOZ aerosol-chemistry-climate model, we show that these aerosols are further transported to the Arctic along isentropic surfaces by the Brewer-Dobson-Circulation (BDC) during the monsoon season. Our model simulations show that East and South Asian anthropogenic emissions contribute significantly to the aerosol transported to the Arctic, which causes a higher negative net aerosol radiative forcing at the surface (dimming) of −0.09 ± 0.02 Wm−2 and −0.07 ± 0.02 Wm−2, respectively. Over the Arctic, the East Asian anthropogenic aerosols that include large amounts of sulfate cause a seasonal mean net radiative forcing at the top of the atmosphere (TOA) of −0.003 ± 0.001Wm−2 and a surface cooling of −0.56 K while the black carbon dominated aerosol from South Asia shows a positive TOA forcing of +0.004 ± 0.001Wm−2 with an only minor surface cooling of −0.043 K. Overall, the long-range transport of South Asian aerosols results in a notably warming throughout the atmospheric column but minimal temperature response at the Arctic surface. Conversely, East Asian aerosols cool the troposphere and heat the lower stratosphere in the Arctic. The Asian aerosol thus plays an ambivalent role, with the East Asian sources in particular having the potential to counteract the rapid rise in Arctic temperatures and the associated melting of snow and ice.
Biased versus unbiased numerical methods for stochastic simulations
Authors: Aguilar Javier , Ramasco José J. , Toral Raúl 
Published: May 2024

AbstractApproximate numerical methods are one of the most used strategies to extract information from many-interacting-agents systems. In particular, numerical approximations are of extended use to deal with epidemic, ecological and biological models, since unbiased methods like the Gillespie algorithm can become unpractical due to high CPU time usage required. However, the use of approximations has been debated and there is no clear consensus about whether unbiased methods or biased approach is the best option. In this work, we derive scaling relations for the errors in approximations based on binomial extractions. This finding allows us to build rules to compute the optimal values of both the discretization time and number of realizations needed to compute averages with the biased method with a target precision and minimum CPU-time usage. Furthermore, we also present another rule to discern whether the unbiased method or biased approach is more efficient. Ultimately, we will show that the choice of the method should depend on the desired precision for the estimation of averages.
Deep seafloor hydrothermal vent communities buried by volcanic ash from the 2022 Hunga eruption
Authors: Beinart Roxanne A. , Arellano Shawn M. , Chaknova Marcus , Meagher Jasper , Davies Andrew J. , Lopresti Joseph , Cowell Emily J. , Betters Melissa , Ladd Tanika M. , Plowman Caitlin Q. , Rice Lauren N. , Davis Dexter , Heffernan Maia , Jimenez Vanessa , Beaver Tessa , Becker Johann , Bergen Sebastien , Brunner Livia , Calhoun Avery , Hauer Michelle , Taradash Aubrey , Giachetti Thomas , Young Craig M. 
Published: May 2024

AbstractMass mortality of marine animals due to volcanic ash deposition is present in the fossil record but has rarely been documented in real time. Here, using remotely-operated vehicle video footage and analysis of ash collected at the seafloor, we describe the devastating effect of the record-breaking 2022 Hunga submarine volcanic eruption on endangered and vulnerable snail and mussel species that previously thrived at nearby deep-sea hydrothermal vents. In contrast to grazing, scavenging, filter-feeding, and predatory vent taxa, we observed mass mortality, likely due to smothering during burial by thick ash deposits, of the foundation species, which rely on symbiotic chemosynthetic bacteria for the bulk of their nutrition. This is important for our broad understanding of the natural disturbance of marine ecosystems by volcanic eruptions and for predicting the effects of anthropogenic disturbance, like deep-sea mining, on these unique seafloor habitats.
Nucleotide sequence as key determinant driving insertions at influenza A virus hemagglutinin cleavage sites
Authors: Spronken Monique I. , Funk Mathis , Gultyaev Alexander P. , de Bruin Anja C. M. , Fouchier Ron A. M. , Richard Mathilde 
Published: May 2024

AbstractHighly pathogenic avian influenza viruses (HPAIVs) emerge from H5 and H7 low pathogenic avian influenza viruses (LPAIVs), most frequently upon insertions of nucleotides coding for basic amino acids at the cleavage site (CS) of the hemagglutinin (HA). The exact molecular mechanism(s) underlying this genetic change and reasons underlying the restriction to H5 and H7 viruses remain unknown. Here, we developed a novel experimental system based on frame repair through insertions or deletions (indels) of HAs with single nucleotide deletions. Indels were readily detected in a consensus H5 LPAIV CS at low frequency, which was increased upon the introduction of only one substitution leading to a longer stretch of adenines at the CS. In contrast, we only detected indels in H6 when multiple nucleotide substitutions were introduced. These data show that nucleotide sequence is a key determinant of insertions in the HA CS, and reveal novel insights about the subtype-specificity of HPAIV emergence.
PRODIGE – Planet-forming disks in Taurus with NOEMA
Authors: Franceschi R. , Henning Th. , Smirnov-Pinchukov G. V. , Semenov D. A. , Schwarz K. , Dutrey A. , Chapillon E. , Gorti U. , Guilloteau S. , Piétu V. , van Terwisga S. , Bouscasse L. , Caselli P. , Gieser G. , Hsieh T.-H. , Lopez-Sepulcre A. , Segura-Cox D. M. , Pineda J. E. , Maureira M. J. , Valdivia-Mena M. T. 
Published: May 2024

Context. To understand how planets form in protoplanetary disks, it is necessary to characterize their gas and dust distribution and masses. This requires a combination of high-resolution dust continuum and molecular line interferometric observations, coupled with advanced theoretical models of protoplanetary disk physics, chemical composition, and radiative transfer.
Aims. We aim to constrain the gas density and temperature distributions as well as gas masses in several T Tauri protoplanetary disks located in Taurus. We use the 12CO, 13CO, and C18O (2–1) isotopologue emission observed at 0.9″ with the IRAM NOrthern Extended Millimeter Array (NOEMA) as part of the MPG-IRAM Observatory Program PRODIGE (PROtostars and DIsks: Global Evolution PIs: P. Caselli & Th. Henning). Our sample consists of Class II disks with no evidence of strong radial substructures. We use these data to constrain the thermal and chemical structure of these disks through theoretical models for gas emission.
Methods. To fit the combined optically thick and thin CO line data in Fourier space, we developed the DiskCheF code, which includes the parameterized disk physical structure, machine-learning (ML) accelerated chemistry, and the RADMC-3D line radiative transfer module. A key novelty of DiskCheF is the fast and feasible ML-based chemistry trained on the extended grid of the disk physical-chemical models precomputed with the ANDES2 code. This ML approach allows complex chemical kinetics models to be included in a time-consuming disk fitting without the need to run a chemical code.
Results. We present a novel approach to incorporate chemistry into disk modeling without the need to explicitly calculate a chemical network every time. Using this new disk modeling tool, we successfully fit the 12CO, 13CO, and C18O (2-1) data from the CI, CY, DL, DM, DN, and IQ Tau disks. The combination of optically thin and optically thick CO lines allows us to simultaneously constrain the disk temperature and mass distribution, and derive the CO-based gas masses. The best-fit disk gas masses range between 0.005 and 0.04 M⊙. These values are in reasonable agreement with the disk dust masses rescaled by a factor of 100 as well as with other indirect gas measurements via, for example, modeling of the wavelength dependence of the dust continuum emission radii, and HD and CO isotopologue emission.
Lithium, rotation and metallicity in the open cluster M35
Authors: Cuenda-Muñoz D. , Barrado D. , Agüeros M. A. , Curtis J. L. , Bouy H. 
Published: May 2024

Context. Lithium (Li) abundance is an age indicator for G, K, and M stellar types, as its abundance decreases over time for these spectral types. However, despite all of the observational efforts made over the past few decades, the role of rotation, stellar activity, and metallicity in the depletion of Li is still unclear.
Aims. Our purpose is to investigate how Li depletion is affected by rotation and metallicity in G and K members of the roughly Pleiades-aged open cluster M35.
Methods. We have collected an initial sample of 165 candidate members observed with the WIYN/Hydra spectrograph. In addition, we have taken advantage of three previous spectroscopic studies of Li in M35. As a result, we have collected a final sample of 396 stars observed with the same instrument, which we have classified as non-members, possible non-members, possible members, and probable members of the cluster. We have measured iron abundances, Li equivalent widths, and Li abundances for the 110 M35 members added to the existing sample by this study. Finally, rotation periods for cluster members have been obtained from the literature or derived from Zwicky Transient Facility light curves.
Results. We have confirmed that fast G and K rotators are Li-rich in comparison with slow rotators of similar effective temperature. This trend, which is also seen in previous studies, is more evident when binaries are not taken into account. Furthermore, while we derived an average metallicity of [Fe/H] = −0.26 ± 0.09 from our spectra, the distribution of Li in M35 is similar to those observed for the Pleiades and M34 open clusters, which have solar metallicity and slightly different ages. In addition, we have shown that an empirical relationship proposed to remove the contribution of the Fe I line at 670.75 nm to the blended feature at 670.78 nm overestimates by 5–15 mÅ the contribution of this iron line for M35 members.
Conclusions. M35 fast G and K rotators have depleted less Li than their slower counterparts. Furthermore, a 0.2−0.3 dex difference in metallicity appears to make little difference in the Li distributions of open clusters with ages between 100 and 250 Myr.
NeuralCMS: A deep learning approach to study Jupiter’s interior
Authors: Ziv M. , Galanti E. , Sheffer A. , Howard S. , Guillot T. , Kaspi Y. 
Published: May 2024

Context. NASA’s Juno mission provided exquisite measurements of Jupiter’s gravity field that together with the Galileo entry probe atmospheric measurements constrains the interior structure of the giant planet. Inferring its interior structure range remains a challenging inverse problem requiring a computationally intensive search of combinations of various planetary properties, such as the cloud-level temperature, composition, and core features, requiring the computation of ∼109 interior models.
Aims. We propose an efficient deep neural network (DNN) model to generate high-precision wide-ranged interior models based on the very accurate but computationally demanding concentric MacLaurin spheroid (CMS) method.
Methods. We trained a sharing-based DNN with a large set of CMS results for a four-layer interior model of Jupiter, including a dilute core, to accurately predict the gravity moments and mass, given a combination of interior features. We evaluated the performance of the trained DNN (NeuralCMS) to inspect its predictive limitations.
Results. NeuralCMS shows very good performance in predicting the gravity moments, with errors comparable with the uncertainty due to differential rotation, and a very accurate mass prediction. This allowed us to perform a broad parameter space search by computing only ∼104 actual CMS interior models, resulting in a large sample of plausible interior structures, and reducing the computation time by a factor of 105. Moreover, we used a DNN explainability algorithm to analyze the impact of the parameters setting the interior model on the predicted observables, providing information on their nonlinear relation.
Entorses do tornozelo no futebol profissional brasileiro: Análise epidemiológica de 126.357 horas de jogo
Authors: Lima Ewerton Borges de Souza , Salgado Gabriel de Melo , Mello Eduardo Patrício , Lara Paulo Henrique Schmidt , Arliani Gustavo Gonçalves , Cohen Moisés 
Published: May 2024

Resumo
Objetivo Realizar análise epidemiológica das entorses de tornozelo em jogadores profissionais de futebol no Brasil.
Métodos Estudo epidemiológico prospectivo das entorses de tornozelo em atletas profissionais de futebol masculino ocorridas no Campeonato Brasileiro e no Campeonato Paulista de Futebol, entre 2016 e 2019. Foram registrados todos os atendimentos médicos em campo realizados durante partidas oficiais. As variáveis avaliadas foram: idade e posição do jogador, diagnóstico da lesão, lateralidade, local em campo onde ocorreu a lesão, tempo de jogo, exames de imagem realizados, realização de tratamento cirúrgico, tempo de afastamento e recorrência da lesão. A incidência das lesões foi avaliada de acordo com a fórmula de incidência da Federation Internationale de Football Association (FIFA).
Resultados As entorses de tornozelo representaram 10,17% do total de lesões, com índice FIFA = 2.002. As lesões ligamentares laterais representaram 53,75% do total das entorses. Os atacantes foram os mais lesionados, com 86 lesões. O meio de campo foi o local com maior número de entorses (75,50%). Nos 15 minutos finais de cada tempo, ocorreram 47,04% das entorses. As lesões foram reincidentes em 31,22% dos casos, e 7,11% das lesões foram tratadas cirurgicamente. O tempo médio de afastamento foi de 13,95 dias.
Conclusões As entorses de tornozelo são lesões frequentes no futebol. Apesar do tempo médio para retorno ao esporte ser breve, essas lesões apresentam grande taxa de reincidência e são potencialmente cirúrgicas, o que está associado a maior tempo de afastamento.
Endovascular Aneurysm Repair (EVAR) in Rupture of the Infrarenal Abdominal Aortic Aneurysm (AAA) with Severe Neck Angulation in Conscience of National Health Coverage in Tertiary Referral Hospital in Indonesian: Case Report
Authors: Nugroho Nyityasmono T. , Primananda Ryoga , Javier R. Mohamad , Fachriza Ihza , Suhartono Raden 
Published: May 2024

AbstractAn aortic aneurysm is a condition with focal dilation of 50% or more over the normal aortic diameter. The most frequent form of aortic aneurysms is infrarenal. Endovascular aortic aneurysm repair is a valid treatment for treating patients with abdominal aortic aneurysm. Abdominal aortic aneurysms (AAAs) are electively repaired to prevent rupture. We present a case of an elderly man with an impending rupture of intraluminal infrarenal AAA with bilateral common iliac arteries aneurysms. Overall, the patient had completed the procedure and made a good postoperative recovery with fully coverage of Indonesian national health insurance.