bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sleep duration associated with feelings but not with test scores: an observational study
Authors: Mehta Kosha J. 
Published: August 2024

AbstractSleep and mood/emotion influence learning and academic achievement. However, inconclusive/contradictory findings have been reported. Unlike previous studies that examined either sleep or mood and grade-point-average (combined result of several assessments over long period), this study examined UK university students for the relationship of test scores with both, previous night’s sleep-duration, and mood/emotion approximately an hour before the test. Mood/feelings data were collected by presenting a selection of emojis and text. Here, test scores did not associate with night sleep-duration. There were no differences in distribution of scores across sleepers of 5, 6, 7 and 8 h and sleeping for less than these hours did not increase the odds of scoring low (scoring ≤ 25%). There was no significant difference in distribution of night-sleep-hours between high scorers (score ≥ 75%) and low scorers (score ≤ 25%). Furthermore, test scores did not associate with feelings/emotions. There were no significant differences in the distribution of scores across different feelings. Unhappy/negative feelings did not increase the odds of scoring low. However, feelings (specifically expressed through selection of words/phrases) predicted scores (p = 0.01) and both negative and positive feelings associated with increased odds of high score (p ≤ 0.04). Night-sleep-duration positively associated with feelings (p < 0.001). Distribution of night-sleep-duration differed between feelings (p ≤ 0.003). Night sleep of less than 5, 6, 7 or 8 h increased the odds of feeling unhappy/negative (p ≤ 0.01). This data (i) defies the generic notion of a night of sub-optimal sleep-duration negatively affecting scores, (ii) provides empirical evidence of association between night-sleep-duration and emotions/mood/feelings, and (iii) proposes that sleep may affect learning via mood.
Contesting coercion: U.S.-China strategic competition, the middle technology trap, and Chinese government-guided funds
Authors: Pan Xuanming , Aiwen Liu , Zhenzhen Chen 
Published: August 2024

AbstractThis study examines the possible emergence of a Middle Technology Trap (MTT) in U.S.-China strategic competition through the lens of the Global Financial Network (GFN) and the Global Innovation Network (GIN). By conducting doctrinal analysis, theoretically informed case studies, and in-depth interviews, we offer a granular study into how the U.S. has been weaponizing its leading position in the GFN to affect China’s level of participation in the GIN. Our findings reveal three U.S. tactics to induce the MTT with China: first, leveraging U.S. private equity and venture capital (PEVC) to enhance its technology advantage over China; second, pushing U.S. investors to withdraw from China’s PEVC market, thereby restricting Chinese access to American capital; and third, inducing Advanced Business Services (ABS) supporting innovation and global business to cease or reduce their operations in China, thereby increasing intermediation costs for innovation. Although Chinese government-guided funds (GGFs) have managed to partially mitigate the “funding gap” from the departure of American PEVCs, they have yet to assume the brokerage role previously played by American PEVCs in both the GIF and the GIN. As such, our study contributes to a better understanding and theoretical advancements of the MTT by linking up the scholarship of innovation and finance with financial statecraft.
Abscission in plants: from mechanism to applications
Authors: Li Jiahuizi , Su Shihao 
Published: August 2024

AbstractAbscission refers to the natural separation of plant structures from their parent plants, regulated by external environmental signals or internal factors such as stress and aging. It is an advantageous process as it enables plants to shed unwanted organs, thereby regulating nutrient allocation and ensuring the dispersal of fruits and seeds from the parent. However, in agriculture and horticulture, abscission can severely reduce crop quality and yield. In this review, we summarize the recent advances in plant abscission from the perspectives of developmental and molecular biology, emphasizing the diverse regulatory networks across different plant lineages, from model plants to crops. The sophisticated process of plant abscission involves several overlapping steps, including the differentiation of the abscission zone, activation of abscission, tissue detachment, and formation of a protective layer. Finally, we discuss the potential applications of physiological modifications and genetic manipulations of plant abscission in sustainable agriculture in the future.
State Municipal Associations as Intermediaries in Service Learning
Authors: Zeemering Eric S. 
Published: August 2024

ABSTRACTService-learning courses help students to identify career opportunities and foster civic engagement, but links to projects with local governments may be difficult to forge. State municipal associations are well positioned as intermediaries to link local governments and higher-education institutions, and their historic roots affirm their capacity to invest in the professionalization of the future public-service workforce. Yet, a recent survey of municipal associations revealed limited contact with higher-education institutions for the purpose of engaging students. Examples from Georgia, Iowa, and Washington highlight the potential role that municipal associations can have in the creation of service-learning opportunities for students. The demand for skilled workers in local government necessitates action by municipal associations and educators in political science to expand service-learning opportunities and access to local government.
Predicting Food‐Security Crises in the Horn of Africa Using Machine Learning
Authors: Busker Tim , van den Hurk Bart , de Moel Hans , van den Homberg Marc , van Straaten Chiem , Odongo Rhoda A. , Aerts Jeroen C. J. H. 
Published: August 2024

AbstractIn this study, we present a machine‐learning model capable of predicting food insecurity in the Horn of Africa, which is one of the most vulnerable regions worldwide. The region has frequently been affected by severe droughts and food crises over the last several decades, which will likely increase in future. Therefore, exploring novel methods of increasing early warning capabilities is of vital importance to reducing food‐insecurity risk. We present a XGBoost machine‐learning model to predict food‐security crises up to 12 months in advance. We used >20 data sets and the FEWS IPC current‐situation estimates to train the machine‐learning model. Food‐security dynamics were captured effectively by the model up to 3 months in advance (R2 > 0.6). Specifically, we predicted 20% of crisis onsets in pastoral regions (n = 96) and 20%–50% of crisis onsets in agro‐pastoral regions (n = 22) with a 3‐month lead time. We also compared our 8‐month model predictions to the 8‐month food‐security outlooks produced by FEWS NET. Over a relatively short test period (2019–2022), results suggest the performance of our predictions is similar to FEWS NET for agro‐pastoral and pastoral regions. However, our model is clearly less skilled in predicting food security for crop‐farming regions than FEWS NET. With the well‐established FEWS NET outlooks as a basis, this study highlights the potential for integrating machine‐learning methods into operational systems like FEWS NET.
Simulated Slidequakes: Insights From DEM Simulations Into the High‐Frequency Seismic Signal Generated by Geophysical Granular Flows
Authors: Arran M. I. , Mangeney A. , De Rosny J. , Toussaint R. 
Published: August 2024

AbstractGeophysical granular flows generate seismic signals known as “slidequakes” or “landquakes”, with low‐frequency components whose generation by mean forces is widely used to infer hazard‐relevant flow properties. Many more such properties could be inferred by understanding the fluctuating forces that generate slidequakes' higher frequency components and, to do so, we conducted discrete‐element simulations that examined the fluctuating forces exerted by steady, downslope‐periodic granular flows on fixed, rough bases. Unlike our previous laboratory experiments, our simulations precluded basal slip. We show that, in its absence, simulated basal forces' power spectra have high‐frequency components more accurately predicted using mean shear rates than using depth‐averaged flow velocities, and can have intermediate‐frequency components which we relate to chains of prolonged interparticle contacts. We develop a “minimal model”, which uses a flow's collisional properties to even more accurately predict the high‐frequency components, and empirically parametrize this model in terms of mean flow properties, for practical application. Finally, we demonstrate that the bulk inertial number determines not only the magnitude ratio of rapidly fluctuating and mean forces on a unit basal area, consistent with previous experimental results, but also the relative magnitudes of the high and intermediate‐frequency force components.
Anatomy of the 2022 Scorching Summer in the Yangtze River Basin Using the SINTEX‐F2 Seasonal Prediction System
Authors: Lu Xinyu , Doi Takeshi , Yuan Chaoxia , Luo Jing‐Jia , Behera Swadhin K. , Yamagata Toshio 
Published: August 2024

AbstractIn July and August 2022, the Yangtze River basin (YRB) experienced its hottest summer since 1961. The SINTEX‐F2 seasonal prediction system initialized in early May predicted the hotter‐than‐normal summer due to its successful prediction of central Pacific La Niña, negative Indian Ocean Dipole and the resultant warming in the tropical West Pacific‐East Indian Ocean (TWP_EIO). The common SST forcing explains only about 26% to the heatwave strength, while the internal variations in the anomalous warming in the TWP_EIO and Europe, surplus precipitation in Pakistan, and local land‐air interaction account for approximately 65%, based on the analysis of 108 ensemble members. These factors have collectively increased the maximum temperature over the YRB through the enhancement and westward expansion of western North Pacific subtropical high. Our findings quantify the relative contributions of external forcing and internal variations to the unprecedented hot event, offering insights into its forming mechanism and potential predictability.
Imbalanced Regressive Neural Network Model for Whistler‐Mode Hiss Waves: Spatial and Temporal Evolution
Authors: Chu Xiangning , Bortnik Jacob , Shen Xiao‐Chen , Ma Qianli , Li Wen , Ma Donglai , Malaspina David , Huang Sheng , Hartley David P. 
Published: August 2024

AbstractWhistler‐mode hiss waves are crucial to the dynamics of Earth's radiation belts, particularly in the scattering and loss of energetic electrons and forming the slot region between the inner and outer belts. The generation of hiss waves involves multiple potential mechanisms, which are under active research. Understanding the role of hiss waves in radiation belt dynamics and their generation mechanisms requires analyzing their temporal and spatial evolutions, especially for strong hiss waves. Therefore, we developed an Imbalanced Regressive Neural Network (IR‐NN) model for predicting hiss amplitudes. This model addresses the challenge posed by the data imbalance of the hiss data set, which consists of predominantly quiet‐time background samples and fewer but significant active‐time intense hiss samples. Notably, the IR‐NN hiss model excels in predicting strong hiss waves (>100 pT). We investigate the temporal and spatial evolution of hiss wave during a geomagnetic storm on 24–27 October 2017. We show that hiss waves occur within the nominal plasmapause, and follow its dynamically evolving shape. They exhibit intensifications with 1 and 2 hr timescale similar to substorms but with a noticeable time delay. The intensifications begin near dawn and progress toward noon and afternoon. During the storm recovery phase, hiss intensifications may occur in the plume. Additionally, we observe no significant latitudinal dependence of the hiss waves within |MLAT| < 20°. In addition to describing the spatiotemporal evolution of hiss waves, this study highlights the importance of imbalanced regressive methods, given the prevalence of imbalanced data sets in space physics and other real‐world applications.
Enhancing Winter Wheat Representation in Noah‐MP‐Crop for Improved Dynamic Crop Growth Simulation in the North China Plain
Authors: Wang Fei , Li Yanping , Li Zhenhua , Cai Xitian , Lin Xiaofeng , Guo Lifeng , Han Dongrui , Fang Jingchun 
Published: August 2024

AbstractExplicitly representing the world's most frequently cultivated winter wheat in land surface model (LSM) is important for understanding carbon and energy cycling over cropland and its interactions with climate, which is crucial for global food security. However, in the latest version of Noah‐MP‐Crop LSM, winter wheat is significantly underrepresented. This study improved the winter‐wheat parameterization in Noah‐MP‐Crop model by optimizing the phenological scheme, incorporating vernalization process, and calibrating several key parameters associated with winter wheat photosynthesis and carbon allocations. Focusing on the North China Plain as area representative region, model performance in simulating crop dynamic growth, carbon flux, and energy fluxes was validated at both site and regional scales. Results showed that the simulated phenological development matched well with the real‐world phenological records. A comparison between the simulated results by the default and developed parameterizations revealed the significant improvements in the reproductions of leaf area index (LAI) and gross primary production (GPP). The determination coefficient (R2) value of GPP was increased from 0.15 to 0.46 to 0.39–0.91. Simulations of energy fluxes showed smaller improvements, with R2 values increasing from 0.46 to 0.67 to 0.61–0.84 for latent heat (LE) and 0.18–0.55 to 0.25–0.61 for sensible heat. Additionally, the mean average error of net radiation was reduced. Improvements in spatial and temporal variations of LAI, GPP, and LE in regional simulation were also observed. This work can facilitate incorporating winter wheat cultivation and its interactions with climate system, particularly when coupling the Noah‐MP‐Crop model with the widely used Weather Research and Forecasting model.
Controllable Seismic Velocity Synthesis Using Generative Diffusion Models
Authors: Wang Fu , Huang Xinquan , Alkhalifah Tariq 
Published: August 2024

AbstractAccurate seismic velocity estimations are vital to understanding Earth's subsurface structures, assessing natural resources, and evaluating seismic hazards. Machine learning‐based inversion algorithms have shown promising performance in regional (i.e., for exploration) and global velocity estimations, while their effectiveness hinges on access to large and diverse training data sets whose distributions generally cover the target solutions. Additionally, enhancing the precision and reliability of velocity estimation also requires incorporating prior information, for example, geological classes, well logs, and subsurface structures, but current statistical or neural network‐based methods are not flexible enough to handle such multimodal information. To address both challenges, we propose to use conditional generative diffusion models for seismic velocity synthesis in which we readily incorporate those priors. This approach enables the generation of seismic velocities that closely match the expected target distribution, offering data sets informed by both expert knowledge and measured data to support training for data‐driven geophysical methods. We demonstrate the flexibility and effectiveness of our method through training diffusion models on the OpenFWI data set under various conditions, including class labels, well logs, reflectivity images, and the combination of these priors. The performance of the approach under out‐of‐distribution conditions further underscores its generalization ability, showcasing its potential to provide tailored priors for velocity inverse problems and create specific training data sets for machine learning‐based geophysical applications.
Cyld restrains the hyperactivation of synovial fibroblasts in inflammatory arthritis by regulating the TAK1/IKK2 signaling axis
Authors: Rinotas Vagelis , Iliaki Kalliopi , Pavlidi Lydia , Meletakos Theodore , Mosialos George , Armaka Marietta 
Published: August 2024

AbstractTNF is a potent cytokine known for its involvement in physiology and pathology. In Rheumatoid Arthritis (RA), persistent TNF signals cause aberrant activation of synovial fibroblasts (SFs), the resident cells crucially involved in the inflammatory and destructive responses of the affected synovial membrane. However, the molecular switches that control the pathogenic activation of SFs remain poorly defined. Cyld is a major component of deubiquitination (DUB) machinery regulating the signaling responses towards survival/inflammation and programmed necrosis that induced by cytokines, growth factors and microbial products. Herein, we follow functional genetic approaches to understand how Cyld affects arthritogenic TNF signaling in SFs. We demonstrate that in spontaneous and induced RA models, SF-Cyld DUB deficiency deteriorates arthritic phenotypes due to increased levels of chemokines, adhesion receptors and bone-degrading enzymes generated by mutant SFs. Mechanistically, Cyld serves to restrict the TNF-induced hyperactivation of SFs by limiting Tak1-mediated signaling, and, therefore, leading to supervised NF-κB and JNK activity. However, Cyld is not critically involved in the regulation of TNF-induced death of SFs. Our results identify SF-Cyld as a regulator of TNF-mediated arthritis and inform the signaling landscape underpinning the SF responses.
PDK4-mediated metabolic reprogramming is a potential therapeutic target for neovascular age-related macular degeneration
Authors: Kim Juhee , Jeon Yujin , Son Jinyoung , Pagire Haushabhau S. , Pagire Suvarna H. , Ahn Jin Hee , Uemura Akiyoshi , Lee In-Kyu , Park Sungmi , Park Dong Ho 
Published: August 2024

AbstractAge-related macular degeneration (AMD) causes severe blindness in the elderly due to choroidal neovascularization (CNV), which results from the dysfunction of the retinal pigment epithelium (RPE). While normal RPE depends exclusively on mitochondrial oxidative phosphorylation for energy production, the inflammatory conditions associated with metabolic reprogramming of the RPE play a pivotal role in CNV. Although mitochondrial pyruvate dehydrogenase kinase (PDK) is a central node of energy metabolism, its role in the development of CNV in neovascular AMD has not been investigated. In the present study, we used a laser-induced CNV mouse model to evaluate the effects of Pdk4 gene ablation and treatment with pan-PDK or specific PDK4 inhibitors on fluorescein angiography and CNV lesion area. Among PDK isoforms, only PDK4 was upregulated in the RPE of laser-induced CNV mice, and Pdk4 gene ablation attenuated CNV. Next, we evaluated mitochondrial changes mediated by PDK1-4 inhibition using siRNA or PDK inhibitors in inflammatory cytokine mixture (ICM)-treated primary human RPE (hRPE) cells. PDK4 silencing only in ICM-treated hRPE cells restored mitochondrial respiration and reduced inflammatory cytokine secretion. Likewise, GM10395, a specific PDK4 inhibitor, restored oxidative phosphorylation and decreased ICM-induced upregulation of inflammatory cytokine secretion. In a laser-induced CNV mouse model, GM10395 significantly alleviated CNV. Taken together, we demonstrate that specific PDK4 inhibition could be a therapeutic strategy for neovascular AMD by preventing mitochondrial metabolic reprogramming in the RPE under inflammatory conditions.
CYLD/HDAC6 signaling regulates the interplay between epithelial-mesenchymal transition and ciliary homeostasis during pulmonary fibrosis
Authors: Ni Hua , Chen Miao , Dong Dan , Zhou Yunqiang , Cao Yu , Ge Ruixin , Luo Xiangrui , Wang Yutao , Dong Xifeng , Zhou Jun , Li Dengwen , Xie Songbo , Liu Min 
Published: August 2024

AbstractThe primary cilium behaves as a platform for sensing and integrating extracellular cues to control a plethora of cellular activities. However, the functional interaction of this sensory organelle with epithelial-mesenchymal transition (EMT) during pulmonary fibrosis remains unclear. Here, we reveal a critical role for cylindromatosis (CYLD) in reciprocally linking the EMT program and ciliary homeostasis during pulmonary fibrosis. A close correlation between the EMT program and primary cilia is observed in bleomycin-induced pulmonary fibrosis as well as TGF-β-induced EMT model. Mechanistic study reveals that downregulation of CYLD underlies the crosstalk between EMT and ciliary homeostasis by inactivating histone deacetylase 6 (HDAC6) during pulmonary fibrosis. Moreover, manipulation of primary cilia is an effective means to modulate the EMT program. Collectively, these results identify a pivotal role for the CYLD/HDAC6 signaling in regulating the reciprocal interplay between the EMT program and ciliary homeostasis during pulmonary fibrosis.
Offshore wind and wave energy can reduce total installed capacity required in zero-emissions grids
Authors: Gonzalez Natalia , Serna-Torre Paul , Sánchez-Pérez Pedro A. , Davidson Ryan , Murray Bryan , Staadecker Martin , Szinai Julia , Wei Rachel , Kammen Daniel M. , Sunter Deborah A. , Hidalgo-Gonzalez Patricia 
Published: August 2024

AbstractAs the world races to decarbonize power systems to mitigate climate change, the body of research analyzing paths to zero emissions electricity grids has substantially grown. Although studies typically include commercially available technologies, few of them consider offshore wind and wave energy as contenders in future zero-emissions grids. Here, we model with high geographic resolution both offshore wind and wave energy as independent technologies with the possibility of collocation in a power system capacity expansion model of the Western Interconnection with zero emissions by 2050. In this work, we identify cost targets for offshore wind and wave energy to become cost effective, calculate a 17% reduction in total installed capacity by 2050 when offshore wind and wave energy are fully deployed, and show how curtailment, generation, and transmission change as offshore wind and wave energy deployment increase.
Rp3: Ribosome profiling-assisted proteogenomics improves coverage and confidence during microprotein discovery
Authors: Vieira de Souza Eduardo , L. Bookout Angie , Barnes Christopher A. , Miller Brendan , Machado Pablo , Basso Luiz A. , Bizarro Cristiano V. , Saghatelian Alan 
Published: August 2024

AbstractThere has been a dramatic increase in the identification of non-canonical translation and a significant expansion of the protein-coding genome. Among the strategies used to identify unannotated small Open Reading Frames (smORFs) that encode microproteins, Ribosome profiling (Ribo-Seq) is the gold standard for the annotation of novel coding sequences by reporting on smORF translation. In Ribo-Seq, ribosome-protected footprints (RPFs) that map to multiple genomic sites are removed since they cannot be unambiguously assigned to a specific genomic location. Furthermore, RPFs necessarily result in short (25-34 nucleotides) reads, increasing the chance of multi-mapping alignments, such that smORFs residing in these regions cannot be identified by Ribo-Seq. Moreover, it has been challenging to identify protein evidence for Ribo-Seq. To solve this, we developed Rp3, a pipeline that integrates proteogenomics and Ribosome profiling to provide unambiguous evidence for a subset of microproteins missed by current Ribo-Seq pipelines. Here, we show that Rp3 maximizes proteomics detection and confidence of microprotein-encoding smORFs.